codebase-rag-mcp
codebase-rag-mcp
一个模型上下文协议(MCP)服务器,可将任何本地代码库转变为可查询、可引用溯源的知识库。它基于混合检索器(密集 FAISS + 稀疏 BM25)、可选的重新排序器,以及可替换的 LLM 提供商(NVIDIA、Groq、OpenRouter、Gemini 或任何本地 OpenAI 兼容端点)构建。
状态: 仅脚手架。软件包可安装,CLI 可运行,MCP 服务器可启动并通告一个占位
ping工具。RAG 流水线(摄取 → 解析 → 分块 → 索引 → 检索 → 重排 → 生成)正在此骨架之上增量构建。请参阅DECISIONS.md和FLOW.md。
安装
需要 Python 3.11+。
# Editable install with dev tooling (pytest, ruff, mypy)
pip install -e ".[dev]"这将引入 tree-sitter、FAISS(CPU)、rank-bm25、sentence-transformers、langchain-huggingface / langchain-community、官方 MCP Python SDK,以及用于外部提供商调用的 httpx。
Related MCP server: Grounded Code MCP
配置
复制示例环境文件,并填写你拥有的提供商密钥:
cp .env.example .env
# then edit .env可识别的变量(完整列表请参阅 .env.example):
变量 | 用途 |
| NVIDIA NIM / build API |
| Groq Cloud |
| OpenRouter(多提供商代理) |
| Google Gemini(可选) |
| OpenAI 兼容的本地服务器(Ollama、vLLM、LM Studio 等) |
| 用于本地服务器的模型名称 |
| 本地服务器的可选 bearer 令牌 |
|
|
| 摄取语料库的存放位置(默认 |
| FAISS / BM25 工件持久化位置(默认 |
运行
# Print the version
codebase-rag --version
# Boot the MCP server over stdio (advertises a 'ping' tool today)
codebase-rag serve开发
ruff check . # lint
ruff format --check . # format check
mypy # type-check
pytest # tests位于 .github/workflows/ci.yml 的预配置 GitHub Actions 工作流会在每次推送时运行全部四项。
布局
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)许可证
MIT。请参阅 LICENSE。
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