codebase-rag-mcp
An MCP server that transforms a local codebase into a queryable, citation-grounded knowledge base using hybrid FAISS and BM25 retrieval, with optional reranking and swappable LLM providers.
README
codebase-rag-mcp
A Model Context Protocol (MCP) server that turns any local codebase into a queryable, citation-grounded knowledge base. Built on a hybrid retriever (dense FAISS + sparse BM25), an optional reranker, and a swappable LLM provider (NVIDIA, Groq, OpenRouter, Gemini, or any local OpenAI-compatible endpoint).
Status: scaffold only. The package installs, the CLI runs, and the MCP server boots and advertises a placeholder
pingtool. The RAG pipeline (ingestion → parsing → chunking → indexing → retrieval → reranking → generation) is being built incrementally on top of this skeleton. SeeDECISIONS.mdandFLOW.md.
Install
Requires Python 3.11+.
# Editable install with dev tooling (pytest, ruff, mypy)
pip install -e ".[dev]"
This pulls in tree-sitter, FAISS (CPU), rank-bm25, sentence-transformers, langchain-huggingface / langchain-community, the official MCP Python SDK, and httpx for outbound provider calls.
Configure
Copy the example env file and fill in whichever provider keys you have:
cp .env.example .env
# then edit .env
Recognized variables (see .env.example for the full list):
| Variable | Purpose |
|---|---|
NVIDIA_API_KEY |
NVIDIA NIM / build API |
GROQ_API_KEY |
Groq Cloud |
OPENROUTER_API_KEY |
OpenRouter (multi-provider proxy) |
GEMINI_API_KEY |
Google Gemini (optional) |
LOCAL_MODEL_BASE_URL |
OpenAI-compatible local server (Ollama, vLLM, LM Studio, ...) |
LOCAL_MODEL_NAME |
Model name to use against the local server |
LOCAL_MODEL_API_KEY |
Optional bearer token for the local server |
LOG_LEVEL |
DEBUG / INFO / WARNING / ERROR (default INFO) |
DATA_DIR |
Where ingested corpora live (default ./data) |
INDEX_DIR |
Where FAISS / BM25 artifacts persist (default ./data/index) |
Run
# Print the version
codebase-rag --version
# Boot the MCP server over stdio (advertises a 'ping' tool today)
codebase-rag serve
Develop
ruff check . # lint
ruff format --check . # format check
mypy # type-check
pytest # tests
A preconfigured GitHub Actions workflow at .github/workflows/ci.yml
runs all four on every push.
Layout
src/codebase_rag_mcp/
config.py # python-dotenv loader
cli/main.py # `codebase-rag` entrypoint
mcp/server.py # stdio MCP server (stub)
ingestion/ # file discovery (TBD)
parser/ # tree-sitter AST extraction (TBD)
chunker/ # AST-aware chunking (TBD)
indexing/
vector.py # FAISS dense index (TBD)
bm25.py # rank-bm25 sparse index (TBD)
retrieval/ # hybrid query routing (TBD)
reranker/ # cross-encoder / LLM reranker (TBD)
generation/
providers/ # NVIDIA / Groq / OpenRouter / Gemini / local (TBD)
citations/ # chunk → source citations (TBD)
impact/ # symbol-graph impact analysis (TBD)
License
MIT. See LICENSE.
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