repo-rag 0.1.1

Local RAG indexer and MCP server for AI coding agents (Claude, GPT, Gemini, Cursor, Factory Droid, and more).

repo-rag

Local RAG indexer and MCP server for AI coding agents. Run it once per repo, and every MCP-compatible agent on your machine - Claude Code, Claude Desktop, Cursor, Windsurf, Codex CLI, Gemini CLI, Factory Droid, Antigravity, Aider, Cline, Continue.dev, Zed, and any future AGENTS.md-aware tool - searches your code through the same hybrid keyword + vector index instead of grepping blind.

Quickstart

# Recommended: isolated global CLI via pipx
pipx install repo-rag

# Or inside an existing project venv
pip install repo-rag

cd /path/to/your/repo
rag init
rag rebuild

rag agents setup --all      # writes rules files + MCP configs for every detected agent
rag hooks install           # keep the index fresh on every commit / merge / checkout

That's it. Open Claude Code, Cursor, or any other supported agent and ask "where is auth configured" - the agent will call repo_rag_search first.

repo-rag pulls in lancedb, pyarrow, fastembed, and onnxruntime, so expect roughly 500 MB on disk for the dependency stack regardless of install method. pipx keeps that footprint in one isolated environment instead of every project venv.

What you get

• One index, every agent. Indexed under ~/.repo-rag/<repo-id>/ and shared across every MCP client. No per-tool re-embedding.
• Hybrid retrieval. SQLite FTS5 BM25 keyword search plus LanceDB vector search, merged with configurable weights.
• Local by default. The fastembed backend runs CPU-only ONNX inference with a 384-dim model; no network calls and no API keys.
• Memory across sessions. repo_rag_remember lets agents persist architectural decisions, gotchas, and invariants that survive rag rebuild.
• Background-mode git hooks. Re-indexing happens off the critical path with truncating per-run logs you can --follow.
• Hardware-aware throttling. On Windows, BELOW_NORMAL_PRIORITY_CLASS plus non-P-core affinity keeps your laptop responsive while indexing.

Supported agents

Agent	Rules	MCP auto-write	Docs
Factory Droid	~/.factory/AGENTS.md, <repo>/AGENTS.md	yes	docs/clients/factory.md
Claude Code	~/.claude/CLAUDE.md, <repo>/CLAUDE.md	yes	docs/clients/claude_code.md
Claude Desktop	(none)	yes (per-OS path)	docs/clients/claude_desktop.md
Codex CLI	~/.codex/AGENTS.md, <repo>/AGENTS.md	yes (TOML)	docs/clients/codex.md
Cursor	~/.cursor/rules/repo-rag.mdc, <repo>/.cursor/rules/repo-rag.mdc	yes	docs/clients/cursor.md
Windsurf	~/.codeium/windsurf/global_rules.md, <repo>/.windsurfrules	yes	docs/clients/windsurf.md
Cline	<repo>/AGENTS.md	manual (VS Code settings)	docs/clients/cline.md
Continue.dev	~/.continue/AGENTS.md, <repo>/AGENTS.md	yes	docs/clients/continue.md
Gemini CLI	~/.gemini/GEMINI.md, <repo>/GEMINI.md	yes	docs/clients/gemini.md
Google Antigravity	~/.antigravity/AGENTS.md, <repo>/AGENTS.md	yes	docs/clients/antigravity.md
Aider	~/.aider/CONVENTIONS.md, <repo>/CONVENTIONS.md	reference YAML	docs/clients/aider.md
Zed	<zed-config>/.rules, <repo>/.rules	yes (context_servers)	docs/clients/zed.md
Universal (AGENTS.md)	~/.config/repo-rag/AGENTS.md, <repo>/AGENTS.md	n/a	docs/clients/universal.md

Run rag agents list for a live table of what is detected on your machine.

MCP tools

The server exposed by rag mcp-server advertises five tools (full reference in docs/mcp-tools.md):

Tool	Purpose
repo_rag_search	Primary hybrid search; use instead of Grep / ripgrep / Glob.
repo_rag_get_context	Markdown context pack for a multi-step task.
repo_rag_remember	Persist a durable note for future sessions.
repo_rag_forget	Remove a note by id.
repo_rag_status	Index health summary.

Read-only tools are annotated readOnlyHint=true, idempotentHint=true, openWorldHint=false so MCP clients can auto-approve them in strict trust modes.

Performance highlights

• 3-10 chunks/sec on a typical laptop with the default fastembed model.
• Embedding cache keyed by (provider, model, dim, sha256(content)) makes interrupted rebuilds resume cheaply and lets you switch providers without invalidating the unrelated rows.
• --window-size, --pace-sec, --sequential, --full-speed, and --threads cover every tuning knob from "go as fast as possible" to "do not interfere with anything I am doing".

See docs/performance.md for the full guide.

Configuration

The global config lives at ~/.repo-rag/config.toml. Override per-repo at ~/.repo-rag/<repo-id>/config.toml. Every value can also be set with an environment variable (RAG_EMBEDDING_PROVIDER, REPO_RAG_INDEX_DIR, ...).

Full reference: docs/configuration.md.

Storage layout

~/.repo-rag/
  registry.json
  config.toml
  <repo_id>/
    metadata.sqlite      # files, chunks, FTS5, notes, embedding cache
    lancedb/             # vector store
    cache/
    logs/

Nothing is written inside your repo apart from optional AGENTS.md, CLAUDE.md, etc. (which you can .gitignore or commit, your choice).

Docker

docker pull ghcr.io/ramanan-bala/repo-rag:latest

{
  "mcpServers": {
    "repo-rag": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-v", "~/.repo-rag:/data/.repo-rag",
        "ghcr.io/ramanan-bala/repo-rag:latest"
      ]
    }
  }
}

Troubleshooting

Common gotchas (Windows model load hang, AV interaction on corporate machines, hybrid-CPU thread tuning, MCP server PATH issues, etc.) live in docs/troubleshooting.md.

Contributing

Pull requests welcome. See CONTRIBUTING.md for setup, test, lint, and release-process notes. To add a new agent plugin, follow docs/development.md.

License

MIT. See LICENSE.

Code of Conduct: CODE_OF_CONDUCT.md. Security policy: SECURITY.md.