catlog22

Codexlens Search — AI skill for Claude Code

AI community

Lightweight semantic code search engine — 2-stage vector + FTS + RRF fusion + MCP server for Claude Code.

How to install Codexlens Search

This entry records only its repository, not the path inside it, so there is no exact command to give. Open catlog22/codexlens-search and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Codexlens Search does

Lightweight semantic code search engine — 2-stage vector + FTS + RRF fusion + MCP server for Claude Code.

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README

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](README_zh.md)

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]