带有 MCP 服务器的语义代码搜索引擎，用于 Claude 代码。

混合搜索：向量 + FTS + AST 图 + ripgrep 正则式——带有 RRF 融合和重新排序。

中文文档

快速启动

添加到你的项目 .mcp.json：

就这样。Claude Code 会自动发现工具：index_project -> Search -> locate。

要启用LLM增强搜索（locate），请添加LLM API密钥：

安装

选择与你平台相匹配的安装方式：

平台推荐

注意：在Windows上，如果你安装了没有[directml]的基础包，MCP服务器会自动检测缺失的GPU运行时，并在第一次启动时安装onnxruntime-directml。GPU从第二次启动起生效。

codexlens-search

Semantic code search engine with MCP server for Claude Code.

Hybrid search: vector + FTS + AST graph + ripgrep regex — with RRF fusion and reranking.

中文文档

Quick Start

pip install codexlens-search[all]

Add to your project .mcp.json:

{
  "mcpServers": {
    "codexlens": {
      "command": "uvx",
      "args": ["--from", "codexlens-search[all]", "codexlens-mcp"],
      "env": {
        "CODEXLENS_EMBED_API_URL": "https://api.openai.com/v1",
        "CODEXLENS_EMBED_API_KEY": "${OPENAI_API_KEY}",
        "CODEXLENS_EMBED_API_MODEL": "text-embedding-3-small",
        "CODEXLENS_EMBED_DIM": "1536"
      }
    }
  }
}

That’s it. Claude Code will auto-discover the tools: index_project -> Search -> locate.

To enable LLM-enhanced search (locate), add LLM API keys:

{
  "mcpServers": {
    "codexlens": {
      "command": "uvx",
      "args": ["--from", "codexlens-search[all]", "codexlens-mcp"],
      "env": {
        "CODEXLENS_EMBED_API_URL": "https://api.openai.com/v1",
        "CODEXLENS_EMBED_API_KEY": "${OPENAI_API_KEY}",
        "CODEXLENS_EMBED_API_MODEL": "text-embedding-3-small",
        "CODEXLENS_EMBED_DIM": "1536",
        "CODEXLENS_LLM_EXPAND_API_KEY": "${GLM_API_KEY}",
        "CODEXLENS_LLM_EXPAND_MODEL": "glm-5-turbo",
        "CODEXLENS_LLM_EXPAND_API_BASE": "https://open.bigmodel.cn/api/paas/v4/"
      }
    }
  }
}

Install

Choose the install that matches your platform:

# Minimal — CPU inference (fastembed bundles onnxruntime CPU)
pip install codexlens-search

# Windows GPU — DirectML, any DirectX 12 GPU (NVIDIA/AMD/Intel)
pip install codexlens-search[directml]

# Linux/Windows NVIDIA GPU — CUDA (requires CUDA + cuDNN)
pip install codexlens-search[cuda]

# Auto-select — DirectML on Windows, CPU elsewhere
pip install codexlens-search[all]

Platform Recommendations

Note: On Windows, if you install the base package without [directml], the MCP server will auto-detect the missing GPU runtime and install onnxruntime-directml on first launch. GPU takes effect from the second start.

What’s Included

All install variants include:

• MCP server — codexlens-mcp command
• AST parsing — tree-sitter symbol extraction + graph search
• USearch — high-performance HNSW ANN backend (default)
• FAISS — ANN + binary index backend (Hamming coarse search)
• File watcher — watchdog auto-indexing