codebase-rag-mcp
codebase-rag-mcp
로컬 코드베이스를 쿼리 가능하고 인용 기반의 지식 베이스로 바꿔주는 Model Context Protocol(MCP) 서버입니다. 하이브리드 검색기(밀집 FAISS + 희소 BM25), 선택적 리랭커, 그리고 교체 가능한 LLM 공급자(NVIDIA, Groq, OpenRouter, Gemini, 또는 모든 로컬 OpenAI 호환 엔드포인트)를 기반으로 구축되었습니다.
상태: 스캐폴드만 존재합니다. 패키지는 설치되고, CLI는 실행되며, MCP 서버는 부팅되어 플레이스홀더
ping도구를 광고합니다. RAG 파이프라인(수집 → 파싱 → 청킹 → 인덱싱 → 검색 → 리랭킹 → 생성)은 이 스켈레톤 위에 점진적으로 구축 중입니다.DECISIONS.md및FLOW.md를 참조하세요.
설치
Python 3.11+ 필요.
# Editable install with dev tooling (pytest, ruff, mypy)
pip install -e ".[dev]"이 명령은 tree-sitter, FAISS(CPU), rank-bm25, sentence-transformers, langchain-huggingface / langchain-community, 공식 MCP Python SDK, 그리고 아웃바운드 공급자 호출용 httpx를 가져옵니다.
Related MCP server: Grounded Code MCP
구성
예제 env 파일을 복사하고 보유한 공급자 키를 입력하세요:
cp .env.example .env
# then edit .env인식되는 변수(전체 목록은 .env.example 참조):
변수 | 용도 |
| NVIDIA NIM / build API |
| Groq Cloud |
| OpenRouter(다중 공급자 프록시) |
| Google Gemini(선택 사항) |
| OpenAI 호환 로컬 서버(Ollama, vLLM, LM Studio, ...) |
| 로컬 서버에 사용할 모델 이름 |
| 로컬 서버용 선택적 bearer 토큰 |
|
|
| 수집된 코퍼스가 저장되는 위치(기본값 |
| FAISS / BM25 아티팩트가 유지되는 위치(기본값 |
실행
# Print the version
codebase-rag --version
# Boot the MCP server over stdio (advertises a 'ping' tool today)
codebase-rag serve개발
ruff check . # lint
ruff format --check . # format check
mypy # type-check
pytest # tests.github/workflows/ci.yml에 미리 구성된 GitHub Actions 워크플로가 모든 푸시마다 네 가지를 모두 실행합니다.
구조
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)라이선스
MIT. LICENSE 참조.
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