Provides structural code intelligence via 26 MCP tools, enabling AI assistants to query code symbols, dependencies, and call graphs accurately without file-pasting.
CodeGraph MCP is a powerful standalone tool that parses your entire C/C++ codebase into a semantic knowledge graph and seamlessly exposes it to AI coding assistants via the Model Context Protocol (MCP).
By providing AI (like Claude Desktop, Cursor, or Google Antigravity) with a structural map of your project—including caller/callee relationships, file dependencies, and dynamic function definition
Provides code intelligence for AI coding agents by indexing repositories into a hybrid knowledge graph, enabling agents to query dependencies, impact, and context through 28 MCP tools.
Enables AI coding assistants to understand codebase architecture in real time by parsing source code into a relationship graph and exposing call chains, dependencies, class hierarchies, and conventions via MCP tools.
Provides AI agents with a function-level dependency graph of the codebase through 30 MCP tools, enabling structural queries about code dependencies, callers, and impact analysis.
Enables AI agents to search code by meaning, explore codebase structure, store and query knowledge with temporal facts, and read source code through a set of MCP tools.