Structural graph memory for AI coding assistants navigate any codebase by structure, not guesswork.
repo-graph gives AI coding assistants a structural map of your codebase β entities, relationships, and end-to-end feature flows β so they navigate straight to the files that matter instead of grepping and reading everything first. It scans your repo once and builds a lightweight graph of what exists (modules, classes, functions, routes, services, components), how things connect (imports, calls, handles, cross-stack HTTP), and where each feature begins and ends. The assistant queries that graph through 11 MCP tools (status, flow, trace, impact, activate, find, dense_text, graph_view, β¦), finds the minimal set of files for the task, and reads only those. Works across 20+ languages and frameworks (Go, Rust, TypeScript/React/Angular/Vue, Python, Java, C#, and more), with cross-stack linking between frontend calls and backend routes. The engine is native Rust shipped as a prebuilt wheel, so scans are fast β a 12,000-node repo maps in a couple of seconds. Controlled before/after on a Go+Angular bug fix, same model and prompt: 2.5Γ fewer tokens and ~9Γ faster with repo-graph installed.
File location: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpRepoGraph": {
"command": "uvx",
"args": [
"mcp-repo-graph",
"--repo",
"/path/to/your/project"
]
}
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