James-Chahwan/repo-graph
by Various
Structural graph memory for AI coding assistants — MCP server for codebase navigation
MCP
James-Chahwan/repo-graph
Added 1 June 2026
Overview
An MCP server written in Rust that provides structural graph memory for AI coding assistants. It models a codebase as a graph of files, functions, and relationships to enable context-aware navigation during code generation and analysis.
Best for
Best for
Developers using MCP-compatible AI coding assistants who need structured context from their codebase.
Use cases
- Give an AI coding assistant a structured graph of the entire codebase
- Improve code generation accuracy by supplying relevant code relationships
- Navigate large or unfamiliar repositories quickly through graph queries
How to use
Install
uvx mcp-repo-graph install Tools exposed
repo-graph
Tested with
VS Code, VS Code Insiders, Cursor
Notes
An MCP server written in Rust that provides structural graph memory for AI coding assistants. It models a codebase as a graph of files, functions, and relationships to enable context-aware navigation during code generation and analysis.
5 stars on GitHub. Last updated 2026-05-22. Licensed MIT.
Use cases
- Give an AI coding assistant a structured graph of the entire codebase
- Improve code generation accuracy by supplying relevant code relationships
- Navigate large or unfamiliar repositories quickly through graph queries
Pros
- Lightweight and performant due to Rust implementation
- Integrates via the standard Model Context Protocol
- Open source and free to use
Cons
- Very early stage with minimal adoption (only 5 stars on GitHub)
- Limited documentation and community support
- Unclear compatibility with languages beyond the tool’s own Rust parsing
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Lightweight and performant due to Rust implementation
- Integrates via the standard Model Context Protocol
- Open source and free to use
Cons
- Very early stage with minimal adoption (only 5 stars on GitHub)
- Limited documentation and community support
- Unclear compatibility with languages beyond the tool's own Rust parsing
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