Full-link intelligent burying point processing system and method

Abstract

This application discloses a full-link intelligent event tracking system and method, relating to the fields of game development and data analysis technology. The system includes: a large model scheme generation module, a scheme review and management module, an IDE integrated development assistant module, and an MCP server. This application constructs a bidirectional direct gRPC connection channel between the "IDE-built-in MCP client" and the "independently deployed backend MCP server," placing data verification at the coding stage and significantly shortening the problem feedback cycle. Combined with a standardized scheme for large model generation and a dynamic rule engine, it constructs a full-link automated closed loop from scheme design and automatic code generation to real-time verification and feedback optimization, significantly improving event tracking development efficiency and data quality. Furthermore, it achieves intelligent data governance through a continuous learning mechanism.

Description

Technical Field

[0001] This application relates to the fields of game development and data analysis technology, and in particular to a full-link intelligent data tracking system and method. Background Technology

[0002] Data tracking, acting as a bridge connecting user behavior and business analysis, plays a crucial role in current game development and operation. The accuracy, completeness, and timeliness of the collected data directly determine the scientific validity and effectiveness of subsequent user profile construction, business monitoring, and product optimization decisions. With increasingly complex business scenarios, the industry has raised higher technical requirements for the standardization and automation of the entire data tracking process, urgently necessitating a management mechanism that can span the entire lifecycle from requirement design and code implementation to data acceptance.

[0003] However, existing event tracking technologies typically exhibit a segmented workflow: event tracking solutions often rely on human experience and are designed using separate documentation tools. Developers must manually write code or integrate SDKs to adapt to different platforms, while data verification is severely delayed. Developers usually need to manually verify data or write scripts to perform checks during application release or testing phases. This workflow results in solution design, code development, and data verification operating in separate tool environments. A technological gap exists between the development environment (IDE) and the backend data verification service, making real-time data compliance checks impossible.

[0004] The toolchain isolation and process fragmentation of existing technologies force the data verification process to be postponed until after development is completed. Developers cannot detect data definition errors or format deviations in real time during the coding phase. They have to go through a lengthy feedback loop of "coding-reporting-switching platforms for verification-re-fixing", which means that data problems are often exposed in the later stages of development or even after going live. This greatly increases the cost and time required to fix problems and makes it difficult to meet the technical requirements of full-process automation and real-time quality assurance.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main purpose of this application is to provide a full-link intelligent event tracking system and method, which aims to solve the technical problems of severe disconnect between existing event tracking development and data verification processes, delayed feedback, and fragmented tools.

[0007] To achieve the above objectives, this application proposes a full-link intelligent data tracking system, the system comprising: The large model solution generation module is used to receive business requirements and call the large language model to generate standardized tracking solutions. The solution review and management module is used to conduct multi-role collaborative review of the tracking solution, and after the review is approved, it is assigned a unique version number and stored in the versioned solution library. The IDE integrated development assistant module is embedded in the development environment as a plugin. It is used to obtain the target version of the tracking scheme from the versioned scheme library and generate or embed tracking code in the development project based on the tracking scheme. The IDE integrated development assistant module integrates an MCP client. The MCP server, deployed independently on the backend, is used to dynamically generate verification rules and perform data verification based on the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol; The IDE integrated development assistant module is also used to respond to the user's verification trigger operation within the development environment, call the MCP client to send the data to be verified to the MCP server through the bidirectional communication connection, and receive the verification result returned by the MCP server for visual feedback.

[0008] In one embodiment, the large language model called by the large model scheme generation module is a large language model pre-trained based on game tracking samples, used for: Receive natural language descriptions of the game type and core analysis scenario as input; The system guides the large language model to output a standardized JSON-formatted event tracking scheme, which includes event definitions, event attribute definitions, and business rule definitions. Simultaneously generate design principle descriptions for each event and event attribute, which are used to explain business considerations and expected analytical value; The aforementioned data collection scheme and design principle description are output to the scheme review and management module.

[0009] In one embodiment, the IDE integrated development assistant module is further configured to perform abstract syntax tree analysis on the current development project before generating or embedding the tracking code, and determine the insertion location of the code in combination with the context of the current development project and the tracking scheme, and handle code conflicts.

[0010] In one embodiment, the MCP server is further configured to respond to a verification request by loading a corresponding event tracking scheme from the versioned scheme library based on the unique version number in the verification request, dynamically generating a verification rule set using a rule engine, and performing verification based on the verification rule set; wherein the verification type of the verification rule set includes at least one or more of the following: syntax compliance verification, simulated data format verification, business rule verification, and mandatory field integrity check.

[0011] In one embodiment, the gPRC bidirectional communication connection between the MCP client and the MCP server adaptively adopts either a long connection or a short connection based on the verification request frequency; the MCP server further includes an identity authentication module, a traffic isolation module, and a rate limiting and degradation module for secure verification of the gPRC bidirectional communication connection.

[0012] In one embodiment, the system further includes an SDK automatic integration module, the SDK automatic integration module being used for: Read the approved event tracking plan; Based on the preset target platform configuration, parse the event definitions and event attribute definitions in the event tracking scheme; Automatically generate client SDK code packages, integration guides, and API documentation for at least one of the following platforms: iOS, Android, and Unity; The IDE integrated development assistant module automatically imports the current development project and scans for dependent configuration files, then imports the client SDK code package into the current development project.

[0013] Furthermore, to achieve the above objectives, this application also proposes a full-link intelligent data tracking method, the method comprising: Receive business requirements and call the large language model to generate standardized event tracking solutions; The aforementioned tracking scheme undergoes multi-role collaborative review, and a unique version number is assigned and stored in the versioned scheme library after the review is approved. The IDE integrated development assistant module embedded in the development environment obtains the target version of the tracking scheme from the versioned scheme library, and generates or embeds tracking code in the development project based on the tracking scheme; wherein, the IDE integrated development assistant module integrates an MCP client; The MCP server, independently deployed in the backend, dynamically generates verification rules and performs data verification according to the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol; In response to the user's verification trigger operation in the development environment, the MCP client is invoked to send the data to be verified to the MCP server through the bidirectional communication connection, and the verification result returned by the MCP server is received and visualized.

[0014] In one embodiment, the step of generating or embedding tracking code in a development project based on the tracking scheme includes: Perform abstract syntax tree analysis on the current development project; The code insertion location is determined by combining the current development project context and the event tracking scheme, and code conflicts are handled.

[0015] In one embodiment, the step of the MCP server performing data verification includes: In response to the verification request sent by the MCP client, the corresponding tracking scheme is loaded from the versioned scheme library according to the unique version number in the verification request; A set of validation rules is dynamically generated using a rule engine, and validation is performed based on the set of validation rules. The validation types of the set of validation rules include at least one or more of the following: syntax compliance validation, simulated data format validation, business rule validation, and mandatory field integrity check.

[0016] In one embodiment, the step of establishing a bidirectional communication connection between the MCP client and the MCP server via the gPRC protocol includes: Based on the frequency of verification requests, a long connection or a short connection is used to establish a bidirectional gPRC communication connection between the MCP client and the MCP server. During communication, the security verification of the gPRC two-line communication connection is performed through the MCP server, which performs identity authentication, traffic isolation, and rate limiting and degradation processing.

[0017] This application proposes a full-link intelligent event tracking system, comprising: a large model scheme generation module for receiving business requirements and generating standardized event tracking schemes by calling a large language model; a scheme review and management module for performing multi-role collaborative review of the event tracking schemes, assigning a unique version number after approval, and storing it in a versioned scheme library; an IDE integrated development assistant module, embedded in the development environment as a plugin, for obtaining the target version of the event tracking scheme from the versioned scheme library, and generating or embedding event tracking code in the development project based on the event tracking scheme; wherein, the IDE integrated development assistant module integrates an MCP client; an MCP server, independently deployed on the backend, for dynamically generating verification rules and performing data verification according to the event tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection via the gPRC protocol; the IDE integrated development assistant module is also used to respond to user verification trigger operations within the development environment, calling the MCP client to send the event tracking data to be verified to the MCP server through the bidirectional communication connection, and receiving the verification results returned by the MCP server for visual feedback. This application constructs a direct closed-loop architecture between the IDE development environment and the backend verification service, which solves the technical problems of severe separation between the data tracking development and data verification stages, delayed feedback, and fragmented tools in the existing technology. It realizes an immersive closed-loop experience of "development is verification". Developers can discover and correct errors in data format, business logic, etc. in real time during the coding stage without leaving the IDE environment, which significantly improves the efficiency of data problem repair. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the module structure of the end-to-end intelligent data embedding system according to an embodiment of this application; Figure 2 This is a flowchart illustrating an embodiment of the end-to-end intelligent data tracking system of this application. Figure 3 This is a flowchart illustrating Embodiment 2 of the full-link intelligent data embedding system of this application; Figure 4 This is a flowchart illustrating Embodiment 3 of the full-link intelligent data embedding processing method of this application.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] Existing technologies suffer from technical problems such as a severe disconnect between data tracking development and data verification, delayed feedback, and fragmented tools.

[0025] This application provides a solution that constructs a direct-connection closed-loop architecture between the IDE development environment and the backend verification service. Specifically, a lightweight MCP client is embedded within the IDE's integrated development assistant module, establishing a bidirectional gRPC communication connection with an independently deployed backend MCP server. Simultaneously, a versioned solution library serves as the sole source of fact, driving automatic code generation on the IDE side and dynamic rule generation on the server side. When a developer triggers verification in the IDE, the system directly sends simulated data to the backend via the direct connection, leveraging the backend's powerful computing capabilities to perform real-time verification and instantly feeding the results back to the IDE interface, achieving an immersive closed-loop experience of "development is verification."

[0026] Based on this, the embodiments of this application provide a full-link intelligent data tracking system, referring to... Figure 1 , Figure 1 This is a schematic diagram of the module structure of the end-to-end intelligent data embedding system of this application.

[0027] In this embodiment, the end-to-end intelligent data tracking system includes: The large model solution generation module 10 is used to receive business requirements and call the large language model to generate standardized tracking solutions.

[0028] It should be noted that, in this embodiment, the large-scale model scheme generation module is the core functional unit responsible for the initial design of the tracking scheme in the system. As the starting point of the entire data processing flow, it aims to solve the problems of low efficiency and inconsistent standards in traditional manual scheme design. Business requirements refer to descriptive information in natural language form input by operations personnel or product managers regarding game type, core analysis scenarios, etc., such as "design a payment analysis tracking scheme for an MMORPG game." The large-scale language model refers to a pre-trained deep neural network model based on the Transformer architecture, such as GPT-4 or Qwen. This model has been fine-tuned with massive amounts of tracking sample data from the game industry and has the ability to understand complex business logic and output structured data. A standardized tracking scheme refers to a data collection specification using a preset format (such as JSON format), specifically including event definitions, event attribute definitions, user attribute definitions, and business rule definitions to provide a unique source of fact. This module guides the large-scale language model to act as an expert through prompting engineering, automatically transforming unstructured business requirements into structured technical solutions, significantly improving the efficiency and standardization of scheme design.

[0029] In one specific implementation, the operations staff inputs a business requirement into the system interface: "Design relevant tracking points for alliance battles in a certain SLG game, and analyze the participation rate and reasons for victory or defeat." After receiving this requirement, the large model solution generation module calls a finely tuned large language model. The model searches for similar historical solutions in the knowledge base and automatically generates a standardized JSON solution containing events such as "event_alliance_war_start (alliance battle start)" and "event_alliance_war_result (alliance battle result)". It also specifies the required attributes for each event (such as alliance ID, battle result, etc.) and business rules (such as only triggering reporting for members who have been in an alliance for more than 24 hours), realizing the automated conversion from natural language to technical specifications.

[0030] The scheme review and management module 20 is used to conduct multi-role collaborative review of the tracking scheme, and assign a unique version number after the review is approved and store it in the versioned scheme library.

[0031] It should be noted that, in this embodiment, the solution review management module is an interactive platform for quality control and process management of generated solutions, aiming to ensure the business rationality and technical feasibility of the tracking solutions. Multi-role collaborative review refers to an online approval process involving personnel from different positions such as operations, data analysts, and product managers. Each role evaluates the solution from different dimensions (such as business value, data specifications, and development costs). A unique version number refers to a code automatically generated by the system to identify the iteration status of a specific tracking solution, such as "v1.0.0," ensuring the accuracy of the solutions referenced in the development and verification stages. A versioned solution library refers to a database system that centrally stores all historical and currently available solutions, supporting version backtracking and difference comparison functions, serving as the data hub of the entire system. This module, through a standardized review process, filters out potential logical defects in solutions generated from large language models, and all modifications to the tracking solutions generate a new unique version number, ensuring the stability and traceability of the solutions referenced during development. In one possible implementation, when a review fails, the solution review management module supports automatically triggering the generation of correction suggestions or draft corrections based on the rejection opinions, for secondary review by the reviewers.

[0032] Additionally, it should be noted that the solution review and management module is also used to maintain the lifecycle status of solutions. Only solutions marked as "available" can be called by the development process, thereby ensuring the consistency of development basis.

[0033] The IDE integrated development assistant module 30 is embedded in the development environment as a plugin. It is used to obtain the target version of the tracking scheme from the versioned scheme library and generate or embed tracking code in the development project based on the tracking scheme. The IDE integrated development assistant module integrates an MCP client.

[0034] It should be noted that, in this embodiment, the IDE integrated development assistant module refers to an intelligent auxiliary tool integrated into an integrated development environment (IDE, such as VSCode or IntelliJ IDEA), aiming to seamlessly embed backend solution capabilities and verification capabilities into the developer's coding workflow, realizing "solution as code." The plug-in form of the integrated development environment means that this module exists as a software extension package, allowing developers to use all functions without switching development tools. The target version of the tracking scheme refers to the scheme data of a specific version number specified by the developer based on the current development task. The MCP client refers to a lightweight communication component integrated into the IDE plug-in, lacking verification logic and only responsible for establishing communication connections with the backend, encapsulating requests, and parsing results. Tracking code refers to program code snippets that conform to the tracking scheme definition and are used to collect and report user behavior data. This module, by combining AST (Abstract Syntax Tree) analysis with project context, can intelligently identify code insertion locations and automatically generate compliant code, significantly reducing the error rate of manual coding.

[0035] In one possible implementation, the IDE integrated development assistant module also provides a conversational interface, allowing developers to drive the module to automatically generate and insert code via natural language commands (such as "add a tracking point at the point of successful user login").

[0036] In one specific implementation, the developer opens the Unity game project in VSCode and enters the application ID and unique version number "v1.0.0" through the IDE's integrated development assistant module. The plugin automatically pulls the versioning scheme from the versioning scheme library and scans the current code directory. When the developer writes user upgrade logic, the plugin, combined with AST analysis, identifies the function onLevelUp(), automatically generates a line of tracking code Tracker.track() inside that function, and prompts the developer to confirm whether to insert it. If a variable naming conflict is detected, the plugin will also automatically suggest renaming the variable, achieving intelligent code integration.

[0037] MCP server 40, independently deployed on the backend, is used to dynamically generate verification rules and perform data verification according to the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol.

[0038] It should be noted that in this embodiment, the MCP server refers to a high-performance verification microservice independently deployed on the backend server. It is the core processing node of the entire verification logic, responsible for tasks such as dynamic rule generation, data verification, and anomaly diagnosis. Dynamically generating verification rules means that the MCP server loads a solution from the solution library in real time based on the application ID and unique version number in the request and compiles it into executable verification logic (e.g., using the Drools rule engine), ensuring that the verification standard and solution are synchronized in real time. The gPRC protocol is a high-performance, open-source remote procedure call protocol based on HTTP / 2 and Protocol Buffers, supporting bidirectional streaming communication and ensuring low-latency data transmission. The bidirectional communication connection refers to the persistent or on-demand network channel established between the MCP client and the MCP server, supporting instant round-trip requests and responses. Verification triggering operations refer to test actions initiated by the developer in the IDE, such as clicking the "Verify" button or saving the code. The data points to be verified refer to the test data packets simulated in the development environment. Visual feedback refers to displaying verification results (such as success, failure, and error details) directly in the IDE interface in the form of warning wavy lines, problem panels, or notification pop-ups. This embodiment achieves "verification during development" through a closed-loop chain of "IDE triggering - backend verification - IDE feedback," eliminating data quality issues at the coding stage.

[0039] Additionally, it should be noted that the validation types performed by the MCP server include, but are not limited to, syntax compliance validation, data format validation, business rule pre-validation, and mandatory field integrity checks. In one possible implementation, the MCP server is also configured with traffic isolation and rate limiting mechanisms to allocate independent service instances or thread pools for pre-validation requests from the IDE, avoiding impact on data validation performance in the production environment and ensuring high system availability.

[0040] The IDE integrated development assistant module is also used to respond to the user's verification trigger operation within the development environment, call the MCP client to send the data to be verified to the MCP server through the bidirectional communication connection, and receive the verification result returned by the MCP server for visual feedback.

[0041] It should be noted that in this embodiment, the IDE integrated development assistant module implements closed-loop interaction with the MCP server within the development environment. Verification triggering refers to developers actively initiating verification through various methods, such as right-clicking in the code editing area and selecting "Verify Tracking Points," clicking the "Verify" button in the plugin's dedicated interface, or writing specific instructions in code comments for the assistant to automatically recognize and execute. Calling the MCP client means that after receiving the verification trigger signal, the IDE integrated development assistant module immediately calls its internally integrated MCP client component and transmits the test data or simulated data associated with the code to be verified in the current development environment to the client. "Receiving the verification result returned by the MCP server" means that after the client obtains the verification result from the server, it parses it and sends it back to the IDE integrated development assistant module. This step aims to empower front-end developers with the powerful verification capabilities of the backend in a direct and convenient way, enabling them to obtain immediate and accurate data quality feedback while coding, thereby completely changing the lengthy cycle of "development-run-wait-modify."

[0042] Optionally, when the IDE starts, the plugin establishes a gRPC connection with the MCP server based on the configuration information. When the user triggers verification, the plugin extracts the code snippet to be verified from the current editor context and simulates the generation of a set of event tracking data to be verified (or directly uses the test data input by the user). Then, this data, along with the application identifier and unique version number obtained from the project configuration, is sent out through the MCP client. Finally, after receiving a response with detailed error information, the response is parsed and mapped to the IDE's code diagnostic API (such as VS Code's Diagnostics API), thus visually presenting the problem on the code interface.

[0043] This application constructs a full-link intelligent event tracking system. Through a large model solution generation module and a solution review and management module, it realizes intelligent generation and version management of solutions. It also utilizes the MCP client built into the IDE integrated development assistant module to establish a gRPC bidirectional communication connection with the independently deployed backend MCP server, realizing automatic generation of event tracking code and real-time verification feedback of data during the development stage. It achieves "development is verification", seamlessly embedding backend verification capabilities into the development environment, solving the pain points of fragmented verification, delayed feedback and difficult collaboration in the traditional event tracking process, significantly improving event tracking development efficiency and data quality, and constructing a fully automated closed loop from solution design, code integration to verification feedback.

[0044] Figure 2 This is a flowchart illustrating an embodiment of the end-to-end intelligent data tracking system of this application, with reference to... Figure 2 The large language model called by the large model generation module in this application is a large language model pre-trained based on game tracking samples, used in steps A201-A204: Step A201: Receive the input game type and a natural language description of the core analysis scenario; Step A202: Guide the large language model to output a standardized JSON-formatted event tracking scheme through prompts. The event tracking scheme includes event definitions, event attribute definitions, and business rule definitions. Step A203: Synchronously generate a design principle description for each event and event attribute. The design principle description is used to explain business considerations and expected analytical value. Step A204: Output the embedding scheme and the design principle description to the scheme review and management module.

[0045] It should be noted that in this embodiment, "game type" refers to the specific category of the game product; "core analysis scenario" refers to the key business nodes or user behavior paths that operations personnel focus on, such as payment conversion, new player churn, and dungeon completion; "large-scale language model" refers to a deep neural network model based on the Transformer architecture (such as GPT-4), which has been fine-tuned with over 100,000 tracking point samples covering more than ten game types, possessing accurate business scenario understanding and structured output capabilities; "hint engineering" refers to the technical means of guiding the model to play the role of a "senior game data analyst" by designing specific hint word instruction processes; "event definition" describes the specific name, display name, and business meaning of user behavior; "event attribute definition" details the parameters accompanying the event; and "business rule definition" specifies the conditions for event triggering and the verification logic. Optionally, the hint engineering process includes role setting, task description, tracking point scheme requirements, output format requirements, and quality requirements to ensure that the model output conforms to industry best practices.

[0046] Additionally, it's worth noting that the large-scale model solution generation module simultaneously generates design principle explanations for each event and its attributes while generating the tracking point solution. These explanations articulate the business considerations and expected analytical value behind specific tracking point designs. This mechanism ensures that the generated solution includes not only "what" (the definition of the tracking point) but also "why" (the design intent), such as explaining that "event_item_compound is designed to analyze the participation and churn points of the material synthesis function." This explanatory generation mechanism helps reviewers quickly understand the design intent, significantly improving review efficiency and solution quality, and avoiding misunderstandings caused by traditional solutions designed solely based on human experience.

[0047] Additionally, it's worth noting that the large-scale model solution generation module ultimately outputs the tracking point scheme and design principle explanation to the solution review and management module. This process aims to transform unstructured business requirements into standardized sources of technical facts, providing a unique basis for the automatic generation of tracking point code and the generation of server-side verification rules. Through this process, the system achieves automated conversion from natural language requirements to standardized technical solutions, solving the problems of low efficiency and inconsistent standards in traditional manual design. Furthermore, by introducing an interpretable generation mechanism, it reduces the communication costs of multi-party collaboration.

[0048] In one possible implementation, the IDE integrated development assistant module is also used to perform abstract syntax tree analysis on the current development project before generating or embedding the tracking code, and to determine the insertion location of the code in combination with the context of the current development project and the tracking scheme, and to handle code conflicts.

[0049] It should be noted that in this embodiment, abstract syntax tree analysis involves parsing the source code of the specified code directory and associated files in the current project, converting it into a tree-like structure to gain a deeper understanding of the code's syntax structure, function call relationships, and variable scope. The IDE integrated development assistant module combines the abstract syntax tree analysis results, the current development project context, and the tracking scheme obtained from the versioning scheme library to intelligently determine the optimal insertion position for the tracking code. The current development project context refers to the environment information such as variables, function logic, and class structure defined in the current code file. This embodiment aims to simulate the coding thinking of experienced developers, accurately locate the execution nodes of business logic (e.g., inside the callback function after successful user login), automatically generate and insert tracking code that conforms to project specifications, thereby ensuring the accuracy and timeliness of data collection, avoiding the inefficiency and omissions of manually searching for insertion positions, and achieving automated conversion of "scheme as code."

[0050] Additionally, it's worth noting that the IDE integrated development assistant module also has the capability to handle code conflicts during code generation and embedding. Code conflicts refer to issues such as duplicate tracking points, variable naming conflicts, or logic overriding that may exist between newly inserted tracking code and existing code. In one possible implementation, when the system detects a potential code conflict, it automatically triggers a conflict warning interface and provides developers with solutions for automatic code merging or manual adjustments, effectively reducing the risk of errors introduced by manual coding and ensuring the cleanliness and stability of the project code. In another possible implementation, code conflict resolution includes using business rules defined in the large model generation scheme to perform lightweight business logic conflict checks on the reported data stream.

[0051] In one possible implementation, the MCP server is further configured to respond to a verification request by loading the corresponding event tracking scheme from the versioned scheme library based on the unique version number in the verification request, dynamically generating a verification rule set using a rule engine, and performing verification based on the verification rule set; wherein the verification type of the verification rule set includes at least one or more of the following: syntax compliance verification, simulated data format verification, business rule verification, and mandatory field integrity check.

[0052] It should be noted that in this embodiment, the MCP client is responsible for encapsulating the verification request and parsing the verification structure. Encapsulating the verification request is the process of packaging the simulated event tracking data, application ID, and unique version number generated by the developer in the IDE according to a preset communication protocol (such as gRPC). Parsing the verification structure is the process of converting the binary or JSON stream data returned by the MCP server into a structured result object (including success status, error code, and error details) that can be recognized by the IDE plugin. The versioning scheme library is a central database that stores multiple versions of standardized event tracking definitions. Dynamically generating verification rule sets using a rule engine refers to the server using a rule engine such as Drools to compile and generate verification logic in real time based on the loaded event tracking scheme. For example, the business description of "user level greater than 10" can be compiled into an executable judgment statement.

[0053] Additionally, it should be noted that the validation rule set covers multiple dimensions, including syntax compliance validation, simulated data format validation, business rule validation, and mandatory field completeness checks. Syntax compliance validation checks whether the reported event names and attribute names exist in the scheme definition; simulated data format validation verifies data types (such as int, string), value ranges, and format specifications; business rule validation verifies whether data logic violates preset rules; and mandatory field completeness checks confirm whether mandatory attributes are missing. This multi-dimensional validation ensures data quality. In one possible implementation, the rule engine supports caching of rule compilation results, for example, with a cache validity period of one hour, automatically invalidating when the scheme is updated, thereby ensuring real-time performance while reducing the performance overhead of dynamic compilation.

[0054] Furthermore, it should be noted that the architecture design in this embodiment achieves centralized management of verification logic and a lightweight development experience. The MCP server, as the core processing node, can dynamically adapt to iterative updates of the solution, synchronizing with the latest verification standards without requiring client redeployment. This greatly improves the flexibility and accuracy of data tracking verification and solves the problem of verification rules lagging behind solution updates in traditional processes.

[0055] In one specific implementation, the developer wrote some event tracking code for purchasing items in the IDE and clicked the verification button. The IDE's integrated development assistant module called the built-in MCP client, encapsulating the current application ID "Game001", the unique version number "v1.0", and the simulated data {event_name: "buy_item", item_id: "sword_01", price:"high"} into a gRPC request and sent it to the MCP server. After receiving the request, the MCP server loaded the event tracking scheme from the versioned scheme library based on the unique version number "v1.0". It found that the scheme defined the "price" attribute as an integer, and the required attribute "user_balance" was missing. The MCP server used the Drools rule engine to generate a validation rule for this attribute in real time. After executing the validation, it determined that the data format was incorrect and the required field was missing, and generated a JSON result containing error details and returned it. The MCP client parses the result and highlights the price field in red in the IDE code editor. At the same time, it displays "Type error: should be int" and "Missing required attribute: user_balance" in the issue panel, thus achieving real-time closed-loop verification during the development phase.

[0056] In one possible implementation, the gPRC bidirectional communication connection between the MCP client and the MCP server adaptively adopts either a long connection or a short connection based on the frequency of verification requests; the MCP server further includes an identity authentication module, a traffic isolation module, and a rate limiting and degradation module for secure verification of the gPRC bidirectional communication connection.

[0057] It should be noted that in this embodiment, the gRPC bidirectional communication connection between the MCP client and the MCP server refers to a high-performance remote procedure call connection based on the HTTP / 2 protocol, used to achieve low-latency data interaction between the IDE plugin and the backend service. The gRPC bidirectional communication connection adaptively uses either long or short connections based on the verification request frequency. Long connections refer to a connection method that can continuously send multiple data packets over a single TCP connection, suitable for high-frequency verification scenarios and avoiding handshake latency caused by frequent connection establishment. Short connections refer to a connection method that disconnects immediately after each data interaction, suitable for low-frequency scenarios and freeing up server resources. Adaptability means that the system can dynamically determine and automatically select the most suitable connection mode based on the real-time verification request frequency. The system dynamically adjusts the connection strategy by monitoring the number of verification requests per unit time to balance communication efficiency and resource consumption. In one possible implementation, when the daily verification requests for a single project exceed a preset threshold, the MCP client automatically uses a gRPC long connection and performs a heartbeat keep-alive; otherwise, it uses short connections created on demand and released after completion. In the event of an unexpected connection interruption, the MCP client also supports an automatic reconnection mechanism. This adaptive mechanism ensures a smooth experience during peak development periods while avoiding the waste of idle resources.

[0058] Additionally, it's worth noting that the MCP server also includes an identity authentication module, a traffic isolation module, and a rate limiting and degradation module, all working together to ensure the security and stability of gRPC bidirectional communication connections. The identity authentication module verifies the legitimacy of the request source. It confirms the operator's identity by verifying the security token, such as its validity, expiration status, and match with the requester's identity. It also distinguishes between the permissions of ordinary developers and administrators; for example, ordinary developers can only initiate pre-verification requests, while administrators have additional advanced permissions such as modifying verification rules and viewing full verification logs. The traffic isolation module configures independent service instances or thread pools for pre-verification requests from the IDE-side MCP client, physically or logically isolating them from the production environment's data verification traffic to prevent interference between different traffic streams and avoid development and testing activities affecting the stability of online business. The rate limiting and degradation module controls the flow of high-concurrency requests, automatically triggering degradation strategies when the system load is too high to ensure the availability of core services. In one possible implementation, the rate limiting and degradation module can be set to a maximum of 10 verification requests per second for a single developer. When the CPU utilization of the MCP server exceeds 80%, a simplified verification result is returned to alleviate computational pressure. These three modules together constitute the security and stability assurance system of the MCP server, aiming to build a secure, reliable, highly available, and high-performance verification service environment. This ensures that the core function of "development as verification" can run stably under any circumstances and will not be interrupted by security attacks, traffic surges, or resource exhaustion.

[0059] In one possible implementation, the traffic isolation module can perform isolation not only on the server side but also in conjunction with the IDE side for traffic identification. For example, when the MCP client initiates a request, it can tag the traffic in the gRPC metadata, such as source:ide, developer_id:zhangsan, project_id:gameX. Based on these tags, the MCP server-side traffic isolation module intelligently distributes requests to the corresponding isolation pools, making the isolation strategy more flexible. For example, it allows setting independent resource quotas for different projects or different developers.

[0060] This application achieves intelligent management and comprehensive security protection of the communication link between the IDE and the backend service by adaptively establishing gRPC long or short connections based on the frequency of verification requests and deploying identity authentication, traffic isolation, and rate limiting / degradation modules on the MCP server. While ensuring a low-latency communication experience, it effectively balances server resource consumption, ensures the security and high availability of the verification service, and avoids high-frequency verification requests from the development environment from interfering with the performance of the production environment through traffic isolation and rate limiting / degradation mechanisms, thus significantly improving the stability of the system.

[0061] Figure 3 This is a flowchart illustrating Embodiment 2 of the end-to-end intelligent data tracking system of this application, with reference to... Figure 3 The end-to-end intelligent data tracking system of this application also includes an SDK automatic integration module, which is used in steps A301-A304: Step A301: Read the approved data tracking plan; Step A302: Based on the preset target platform configuration, parse the event definitions and event attribute definitions in the event tracking scheme; Step A303 automatically generates client SDK code packages, integration guides, and API documentation suitable for at least one of the following platforms: iOS, Android, and Unity. Step A304: The current development project is automatically imported and the dependent configuration files are scanned by the IDE integrated development assistant module, and the client SDK code package is imported into the current development project.

[0062] It should be noted that in this embodiment, the SDK automatic integration module is the core functional unit that transforms standardized solutions into executable code, aiming to solve the problem of tedious and error-prone manual writing of cross-platform event tracking code in traditional development. The SDK automatic integration module reads the approved event tracking solutions, which are standardized data collection specifications that have undergone multi-role collaborative review, are marked as "available," and are stored in a versioned solution library. Target platform configuration refers to the code generation strategy maintained internally by this module for different target platforms. The system automatically adapts the corresponding code template and code generation logic based on the platform type pre-selected by the user (such as checking "Generate iOS SDK" or "Generate Android SDK" through the configuration interface). Based on the parsing results, the system uses the code generation engine to automatically generate client SDK code packages, integration guides, and API documentation suitable for mainstream game development platforms such as iOS, Android, Unity, Unreal Engine, or Cocos. The client SDK code package is an assembly that encapsulates the data collection and reporting logic, while the integration guide and API documentation are explanatory documents to help developers quickly integrate the platform. This embodiment realizes the automated conversion of "solution as code", which solves the core pain points in traditional event tracking development, such as huge workload for cross-platform adaptation, error-prone manual coding, and inconsistency between documentation and code. It ensures the standardization and consistency of event tracking implementation across different platforms and significantly reduces the development cost of cross-platform adaptation.

[0063] Additionally, it should be noted that the IDE integration development assistant module automatically imports the current development project, and the SDK automatic integration module further simplifies the development process. The module automatically scans the configuration files that the current development project depends on. These configuration files are used to manage references to third-party libraries, such as the `build.gradle` file for an Android project or the `manifest` file for a Unity project. Through scanning, the module can identify the environment characteristics of the current project, automatically resolve version compatibility and dependency conflicts, and import the generated client SDK code package into the current development project, eliminating the need for developers to manually download and unzip it. In one possible implementation, if the project environment has network restrictions or special configuration requirements, the system also supports developers manually downloading the SDK package and completing the manual import according to the generated integration guide.

[0064] In one possible implementation, the SDK automatic integration module also supports code reuse and incremental update functions, automatically compares the differences between the old and new solutions, and only generates or modifies the code files of the changed parts; the SDK automatic integration module is linked with the versioned solution library to realize the forced binding of SDK version and solution version and has the ability to adapt to platform differences when generating SDK code.

[0065] Furthermore, embodiments of this application provide a full-link intelligent data tracking method, referring to... Figure 4 , Figure 4 This is a flowchart illustrating Embodiment 3 of the end-to-end intelligent data tracking method of this application; the end-to-end intelligent data tracking method includes steps A401-A405: Step A401: Receive business requirements and call the large language model to generate a standardized event tracking solution; Step A402: Perform multi-role collaborative review of the event tracking scheme, and assign a unique version number after the review is approved and store it in the versioned scheme library. Step A403: Obtain the target version of the tracking scheme from the versioned scheme library through the IDE integrated development assistant module embedded in the development environment, and generate or embed tracking code in the development project based on the tracking scheme; wherein, the IDE integrated development assistant module integrates an MCP client; Step A404: The MCP server, independently deployed in the backend, dynamically generates verification rules and performs data verification according to the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol. Step A405: In response to the user's verification trigger operation in the development environment, the MCP client is invoked to send the data to be verified to the MCP server through the bidirectional communication connection, and the verification result returned by the MCP server is received and visualized.

[0066] It should be noted that this application automatically generates a standardized tracking scheme through a large language model. After multi-role review and version management, the tracking code is automatically generated using the IDE integrated development assistant module. A bidirectional direct gRPC connection channel is established between the IDE-side MCP client and the backend MCP server, enabling real-time verification and visual feedback of reported data within the development environment. For example, the pass rate and error type distribution are statistically analyzed based on project, version, and time dimensions, constructing a fully automated closed loop from requirements to verification. The above scheme realizes "development is verification," placing the data verification stage forward to the coding phase, breaking down the barriers between development and verification in the traditional process, significantly improving the first-pass rate and data quality of the tracking code, and shortening the development and repair cycle. At the same time, through the standardized automatic generation and version management of the scheme, the cost of cross-team collaboration and the rate of human error are effectively reduced, realizing intelligent governance of tracking work.

[0067] In one possible implementation, the step of generating or embedding tracking code in the development project based on the tracking scheme includes: Perform abstract syntax tree analysis on the current development project; The code insertion location is determined by combining the current development project context and the event tracking scheme, and code conflicts are handled.

[0068] It should be noted that the abstract syntax tree analysis in this embodiment parses the source code into an abstract syntax tree. The IDE integrated development assistant module can accurately understand the logical structure of the code, function boundaries, variable scope, and dependencies between statements. This provides a structured code understanding foundation for the accurate positioning of the tracking code, ensuring that the tracking code is inserted in the position that best conforms to the business semantics, while avoiding disruption of the logical integrity of the existing code. In one possible implementation, the IDE integrated development assistant module, based on the triggering conditions defined in the event tracking scheme and the results of the abstract syntax tree analysis, locates functions or code blocks in the code that meet the triggering conditions as candidate insertion positions. Secondly, it scores the candidate positions using heuristic rules (such as prioritizing functions whose names contain "track," "report," or "analytics," or selecting widely used tracking entry functions in the project), selecting the position with the highest score as the final insertion point. Thirdly, after determining the insertion position, conflict detection is performed; if a variable name conflict is detected, a non-conflicting variable name is automatically generated and the developer is prompted for confirmation. Finally, the confirmed tracking code is inserted into the specified position.

[0069] In one possible implementation, the steps of the MCP server performing data verification include: In response to the verification request sent by the MCP client, the corresponding tracking scheme is loaded from the versioned scheme library according to the unique version number in the verification request; A set of validation rules is dynamically generated using a rule engine, and validation is performed based on the set of validation rules. The validation types of the set of validation rules include at least one or more of the following: syntax compliance validation, simulated data format validation, business rule validation, and mandatory field integrity check.

[0070] As should be noted, this embodiment uses the MCP client to handle lightweight request encapsulation and result parsing, while the MCP server dynamically loads the event tracking scheme based on a unique version number and uses a rule engine to generate a multi-dimensional verification rule set in real time. This achieves an automated data verification process covering syntax compliance, data format, business rules, and the completeness of required fields. The above scheme achieves centralized management of verification logic and lightweight client, ensuring real-time synchronization between verification standards and event tracking schemes, and allowing rules to be updated without redeploying the client. Through comprehensive multi-dimensional checks, it effectively intercepts data format errors and business logic defects during the development phase, significantly improving the compliance and accuracy of event tracking data, and supporting an efficient closed loop of "development is verification".

[0071] In one possible implementation, the steps for establishing a bidirectional communication connection between the MCP client and the MCP server via the gPRC protocol include: Based on the frequency of verification requests, a long connection or a short connection is used to establish a bidirectional gPRC communication connection between the MCP client and the MCP server. During communication, the security verification of the gPRC two-line communication connection is performed through the MCP server, which performs identity authentication, traffic isolation, and rate limiting and degradation processing.

[0072] It should be noted that this embodiment optimizes communication efficiency by monitoring the frequency of verification requests and adaptively establishing long or short gRPC connections. It also integrates identity authentication, traffic isolation, and rate limiting / degradation mechanisms on the MCP server, constructing a communication link management system that balances efficient transmission and security protection. This addresses the resource waste caused by fixed connection modes in low-frequency scenarios or performance degradation due to frequent handshakes in high-frequency scenarios, the risk of pre-verification traffic from the development environment impacting the stability of services in the production environment, and the potential for unauthorized access and system overload due to a lack of security controls. It achieves on-demand allocation and efficient utilization of communication resources, ensuring low-latency responses to verification requests. Traffic isolation and rate limiting / degradation effectively prevent the impact of development activities on online services, ensuring high availability of core services. Simultaneously, the identity authentication mechanism ensures the security of data interaction, improving the overall stability and reliability of the system.

[0073] In one possible implementation, the method constructs a tracking knowledge graph to associate tracking schemes, code implementations, verification rules, and application scenarios. The knowledge graph supports querying via the IDE integrated development assistant module or a data analysis platform. This embodiment achieves cross-stage data asset interconnection based on the tracking knowledge graph, breaking down the information fragmentation between stages in traditional processes. This enables developers and operations personnel to quickly trace the tracking design intent and implementation logic; effectively promotes the accumulation and reuse of tracking knowledge across projects and teams, reduces the learning cost and communication threshold for new members, and provides full-link contextual support for data governance and business decisions.

[0074] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the full-link intelligent data tracking method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0075] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0076] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0077] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation that may be implemented in systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0078] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0079] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A full-link intelligent data tracking system, characterized in that, The system includes: The large model solution generation module is used to receive business requirements and call the large language model to generate standardized tracking solutions. The solution review and management module is used to conduct multi-role collaborative review of the tracking solution, and after the review is approved, it is assigned a unique version number and stored in the versioned solution library. The IDE integrated development assistant module is embedded in the development environment as a plugin. It is used to obtain the target version of the tracking scheme from the versioned scheme library and generate or embed tracking code in the development project based on the tracking scheme. The IDE integrated development assistant module integrates an MCP client. The MCP server, deployed independently on the backend, is used to dynamically generate verification rules and perform data verification based on the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol; The IDE integrated development assistant module is also used to respond to the user's verification trigger operation within the development environment, call the MCP client to send the data to be verified to the MCP server through the bidirectional communication connection, and receive the verification result returned by the MCP server for visual feedback.

2. The end-to-end intelligent data tracking system as described in claim 1, characterized in that, The large language model called by the large model generation module is a large language model pre-trained based on game tracking samples, used for: Receive natural language descriptions of the game type and core analysis scenario as input; The system guides the large language model to output a standardized JSON-formatted event tracking scheme, which includes event definitions, event attribute definitions, and business rule definitions. Simultaneously generate design principle descriptions for each event and event attribute, which are used to explain business considerations and expected analytical value; The aforementioned data collection scheme and design principle description are output to the scheme review and management module.

3. The end-to-end intelligent data tracking system as described in claim 1, characterized in that, The IDE integrated development assistant module is also used to perform abstract syntax tree analysis on the current development project before generating or embedding the tracking code, and to determine the code insertion location by combining the current development project context and the tracking scheme, and to handle code conflicts.

4. The end-to-end intelligent data tracking system as described in claim 1, characterized in that, The MCP server is also used to respond to verification requests, load the corresponding tracking scheme from the versioned scheme library according to the unique version number in the verification request, dynamically generate a verification rule set using the rule engine, and perform verification based on the verification rule set; wherein, the verification type of the verification rule set includes at least one or more of the following: syntax compliance verification, simulated data format verification, business rule verification, and mandatory field integrity check.

5. The end-to-end intelligent data tracking system as described in claim 1, characterized in that, The gPRC bidirectional communication connection between the MCP client and the MCP server adaptively adopts either a long connection or a short connection based on the frequency of verification requests. The MCP server also includes an identity authentication module, a traffic isolation module, and a rate limiting and degradation module for secure verification of the gPRC bidirectional communication connection.

6. The end-to-end intelligent data tracking system as described in claim 1, characterized in that, The system also includes an SDK automatic integration module, which is used for: Read the approved event tracking plan; Based on the preset target platform configuration, parse the event definitions and event attribute definitions in the event tracking scheme; Automatically generate client SDK code packages, integration guides, and API documentation for at least one of the following platforms: iOS, Android, and Unity; The IDE integrated development assistant module automatically imports the current development project and scans for dependent configuration files, then imports the client SDK code package into the current development project.

7. A method for intelligent data tracking across the entire data link, characterized in that, The end-to-end intelligent data embedding processing method includes: Receive business requirements and call the large language model to generate standardized event tracking solutions; The aforementioned tracking scheme undergoes multi-role collaborative review, and a unique version number is assigned and stored in the versioned scheme library after the review is approved. The IDE integrated development assistant module embedded in the development environment obtains the target version of the tracking scheme from the versioned scheme library, and generates or embeds tracking code in the development project based on the tracking scheme; wherein, the IDE integrated development assistant module integrates an MCP client; The MCP server, independently deployed in the backend, dynamically generates verification rules and performs data verification according to the data tracking scheme; wherein, the MCP client and the MCP server establish a bidirectional communication connection through the gPRC protocol; In response to the user's verification trigger operation in the development environment, the MCP client is invoked to send the data to be verified to the MCP server through the bidirectional communication connection, and the verification result returned by the MCP server is received and visualized.

8. The end-to-end intelligent data embedding processing method as described in claim 7, characterized in that, Prior to the step of generating or embedding tracking code in the development project based on the tracking scheme, the following steps are included: Perform abstract syntax tree analysis on the current development project; The code insertion location is determined by combining the current development project context and the event tracking scheme, and code conflicts are handled.

9. The end-to-end intelligent data embedding processing method as described in claim 7, characterized in that, The steps for data verification performed by the MCP server include: In response to the verification request sent by the MCP client, the corresponding tracking scheme is loaded from the versioned scheme library according to the unique version number in the verification request; A set of validation rules is dynamically generated using a rule engine, and validation is performed based on the set of validation rules. The validation types of the set of validation rules include at least one or more of the following: syntax compliance validation, simulated data format validation, business rule validation, and mandatory field integrity check.

10. The end-to-end intelligent data embedding processing method as described in claim 7, characterized in that, The steps for establishing a bidirectional communication connection between the MCP client and the MCP server via the gPRC protocol include: Based on the frequency of verification requests, a long connection or a short connection is used to establish a bidirectional gPRC communication connection between the MCP client and the MCP server. During communication, the security verification of the gPRC two-line communication connection is performed through the MCP server, which performs identity authentication, traffic isolation, and rate limiting and degradation processing.

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