Listed on: skills.sh · Glama · mcpservers.org · ghcr.io

🔭 Live demo → — RepoSkein's own graph, rendered as an interactive 3D constellation in your browser.

Get running in one line: Claude Code: /plugin marketplace add reposkein/reposkein · elsewhere: npx @reposkein/mcp init — full walkthrough in Installation.

Introduction

RepoSkein gives your AI coding agent a map of your codebase — so it navigates structure instead of grepping and guessing.

It uses Tree-sitter to build a deterministic Code Property Graph of your repo — files, classes, functions, imports, and call edges — and serves it to any MCP-capable agent (Claude Code, Cursor, Codex, …). As the agent works, it writes short natural-language summaries onto graph nodes; those summaries are versioned in git alongside the code, so an agent's understanding becomes shared team memory that the next agent — or teammate — starts from.

Who it's for: developers using AI coding agents on real, large, or nested/polyglot codebases, who are tired of the agent burning its context window on grep; and teams who want that hard-won understanding to persist and be shared rather than re-derived every session.

• ⚡ Zero-infra — no database, no Docker. The graph lives in plain .reposkein/*.jsonl files, rebuilt from your working tree in seconds.

• 🔒 Deterministic — same code → byte-identical graph. No LLM in the construction path.

• 🌐 7 languages — Python, TypeScript, JavaScript, Rust, Go, Java, C#.

• 🧩 Local-first & git-native — the summaries your agents write are committed and travel with your code.

In a deterministic, no-LLM benchmark, RepoSkein surfaces the right functions with a mean ~8.4× fewer context tokens than a grep-based agent on structural queries.

The bundled reposkein-graph-rag skill drives a semantic_find → get_context_profile → impact → get_temporal_context → write_semantic_summary → reindex_file loop, so you just ask in plain language. Full workflow, an example interaction, and the tool-by-tool + CLI reference: docs/TOOLS.md.

Table of contents

• For teams

• Prerequisites

• Installation

• Supported languages

• Documentation

• Contributing

• Acknowledgements

• Contact

• License

For teams

Joining a repo that already has RepoSkein set up? One command, no questions asked:

git clone <repo-url> && cd <repo> && npx @reposkein/mcp init

init detects the committed .reposkein/meta.json, reuses its config, and wires up your agent's MCP config automatically. Publish a durable, shareable view of the graph with a hosted constellation (GitHub Pages via reposkein-mcp init --ci) — and because summaries are committed to git, they're shared team memory: every teammate's agent starts from what previous agents already learned, not from scratch.

Support: if RepoSkein is useful, Ko-fi support funds hosted-constellation infrastructure and indexer maintenance — supporters get an ad-free experience once sponsorship tiers ship.

Prerequisites

• Node.js 18+ — to run npx @reposkein/mcp (the indexer binary is fetched automatically).

• An MCP-capable agent — Claude Code, Cursor, Codex, Zed, etc.

• A git repository to index (RepoSkein installs git hooks and reads git history for get_temporal_context).

• Optional: Docker (only for the embeddings server or the Neo4j backend); Rust (only to build from source).

Installation

Claude Code? Two commands, zero config:

/plugin marketplace add reposkein/reposkein
/plugin install reposkein

The plugin registers the MCP server against whatever repo you have open (REPOSKEIN_REPO_PATH is wired to the project directory) and ships the navigation skills as /reposkein:reposkein-setup and /reposkein:reposkein-graph-rag — run the setup skill once per repo to build the graph. Optional embeddings (Voyage AI or any OpenAI-compatible endpoint) work by exporting the REPOSKEIN_EMBED_* env vars in your shell — the plugin's server inherits them; the default is fully local, zero-egress lexical search.

Any other agent — in the repo you want it to understand:

npx @reposkein/mcp init

This downloads the indexer for your platform, installs git hooks + the navigation skill, builds the initial code graph, and prints an MCP config block. Then:

1. Add the printed config to your agent (e.g. Claude Code's .mcp.json):

   {
     "mcpServers": {
       "reposkein": {
         "command": "reposkein-mcp",
         "env": { "REPOSKEIN_REPO_PATH": "/path/to/your/repo" }
       }
     }
   }

2. Verify the graph (init already built it):

   reposkein-mcp doctor .         # ✓ binary  ✓ indexed (N nodes)  ✓ ready
   git add .reposkein/meta.json .reposkein/config.toml && git commit -m "add RepoSkein config"

   nodes.jsonl and edges.jsonl are derived from your working tree and git-ignored — a clone rebuilds them on first use. Re-index after big changes with reposkein-mcp index . (or the agent's reindex_file tool).

3. Ask your agent "what calls this function?" or "what breaks if I change X?" — it answers from the graph.

Prefer to let your agent set it up? Install the skills and tell it to run the reposkein-setup skill — it installs, indexes, and verifies everything:

npx skills add reposkein/reposkein --all

Platforms: prebuilt binaries for macOS (Apple Silicon), Linux (x64/arm64), and Windows (x64). Elsewhere, point REPOSKEIN_INDEXER_BIN at a from-source build.

Let your agent install it for you

For complex setups — multi-repo workspaces, Neo4j backend, the local embedding server, or wiring up agents besides Claude Code (OpenCode, Cursor, Codex, Continue, Cline, …) — paste this into any MCP-capable agent and it'll walk you through:

Install RepoSkein in this workspace. Read docs/INSTALL.md (or https://github.com/reposkein/reposkein/blob/main/docs/INSTALL.md), walk me through the question tree in §1, then execute §2 onward. If anything fails, troubleshoot via §9 — don't silently skip steps. Confirm with reposkein-mcp doctor . per repo and a semantic_find smoke test before claiming done.

docs/INSTALL.md is written for agents: it covers the decision tree (one repo vs workspace, JSONL vs Neo4j, lexical vs cloud vs local embeddings, which agent CLIs to wire), per-agent config schemas (.mcp.json, opencode.json, .cursor/mcp.json, Continue, Codex, Cline, …), the Apple-Silicon mps native embed-server recipe, and a troubleshooting table.

Supported languages

Python, TypeScript, JavaScript, Rust, Go, Java, C# — with an honest per-language matrix of what resolves exact vs by-name vs ambiguous. Full table + the resolution rules: docs/ARCHITECTURE.md. Adding a language is a well-trodden path — contributions welcome.

Going deeper: how the graph is built + cross-repo federation · the constellation viewer · semantic embeddings · Neo4j backend · shared remote server · building from source + repo layout.

Documentation

Full index, task-oriented: docs/README.md.

Contributing

Contributions are welcome — bug fixes, new languages, docs. See CONTRIBUTING.md for the dev setup, the determinism invariants you must preserve, and the step-by-step recipe for adding a new language (it's a well-trodden path — Go, Java, and C# were each added the same way). RepoSkein uses Conventional Commits and keeps CI green (determinism gates + clippy + tests).

Acknowledgements

• Tree-sitter — the parsers behind every language extractor.

• Model Context Protocol — the agent integration standard.

• Voyage AI — voyage-code-3 and the open-weight voyage-4-nano powering the optional embeddings tier.

• Discovery via Glama, skills.sh, mcpservers.org, and the awesome-mcp community lists.

• README header by capsule-render.

Contact

• 🐛 Bugs / features: open an issue

• 💬 Questions / ideas: GitHub Discussions

License

Apache-2.0.