Analyzes IL2CPP dump.cs files from Unity games using an agentic RAG system and Model Context Protocol.
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This tool is a specialized Retrieval-Augmented Generation (RAG) system tailored for analyzing IL2CPP dump.cs files extracted from Unity games. It leverages advanced embeddings and integrates with a knowledge retrieval engine to enable developers to query and understand game mechanics and code structure. By implementing the Model Context Protocol (MCP) server specification using the official MCP TypeScript SDK, it ensures standardized interactions with Large Language Model (LLM) clients like Claude and GPT, facilitating agent-based analysis and exploration of game code.
Key Features
01Integrates with Context7 as a knowledge retrieval engine.
02Fully compliant with the Model Context Protocol via the official MCP TypeScript SDK.
03Uses Xenova's Transformers.js for high-quality embeddings.
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05Parses and analyzes IL2CPP dump.cs files.
06Implements an agent architecture for natural language queries.
Use Cases
01Integrating IL2CPP analysis into agent-based workflows.
02Analyzing Unity game code decompiled via IL2CPP.
03Interacting with game code using natural language queries.
