repo-map-mcp
Maintains a self-updating JSON index of repository files, functions, and descriptions so agents can query relevant files instead of grepping the tree.
README
repo-map-mcp
MCP server that maintains a self-updating, per-file JSON index of a repo (directory, filename, description, function names, timestamps) so an agent can query "what's probably relevant" instead of grepping/reading the whole tree.
File exploration and path annotation computed locally; Description and file purpose are dictated by the agent, which provides them even better context.
Install
uv sync
Tools
index_repository(root_path, force=False)— walkroot_path(respecting.gitignore+ hardcoded excludes), hash each file, re-parse function names for changed files, update the on-disk index at<root_path>/.repo-index/index.json. Returns a summary string.get_repo_map(root_path, dir_prefix=None)— return the JSON index, optionally scoped to a subdirectory.search_files(root_path, query)— substring match against filename, description, and function names.get_stale_files(root_path)— files whosedescriptionStaleflag is set, with their function names, so the calling agent can write a description without opening the file.set_description(root_path, path, description)— writes the description back and clears the stale flag.
Supported languages for function extraction (via tree-sitter): Python,
JavaScript, TypeScript, TSX, Java, Rust. Other file types still get
indexed, with funcs: [].
Requirements:
- Python
- uv
Run
uv run repo-map-mcp
Runs on stdio — add it to an MCP client config (e.g. Claude Code) pointing
command at uv run repo-map-mcp (cwd set to this directory, or use an
absolute path).
Test
uv run pytest -q
uv run python3 scripts/smoke_client.py # end-to-end tool call smoke test
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.