Claude 代码的免费本地 RAG - 节省令牌和时间

日本語版はこちら |日语版本

DevRag 是一个轻量级的 RAG（检索增强生成）系统，专为使用 Claude 代码的开发者设计。别再浪费代币阅读整份文档了——让矢量搜索准确找到你需要的内容。

为什么是DevRag？

使用 Claude Code 时，使用阅读工具读取文档会消耗大量代币：

• ❌ 浪费上下文：每次都要读取整个文档（每个文件3,000+标记）
• ❌ 搜索性差：Claude不知道哪个文件包含什么
• ❌ 重复性：同一文档在会话中多次阅读

与DevRag合作：

• ✅ 40x少令牌：向量搜索仅检索相关区块（~200个令牌）
• ✅ 15倍快：搜索时间为100毫秒，阅读时间为30秒
• ✅ 自动发现：Claude Code 无需知道文件名即可查找文档

特色

• 🤖 Simple RAG - Claude 代码的检索增强生成
• 📝 Markdown 支持 - 自动索引 .md 文件
• 🔍 语义搜索 - 自然语言查询，如“JWT 认证方法”
• 🚀 单一二进制 - 无Python，模型首次运行时自动下载

DevRag

Free Local RAG for Claude Code - Save Tokens & Time

日本語版はこちら | Japanese Version

DevRag is a lightweight RAG (Retrieval-Augmented Generation) system designed specifically for developers using Claude Code. Stop wasting tokens by reading entire documents - let vector search find exactly what you need.

Why DevRag?

When using Claude Code, reading documents with the Read tool consumes massive amounts of tokens:

• ❌ Wasting Context: Reading entire docs every time (3,000+ tokens per file)
• ❌ Poor Searchability: Claude doesn’t know which file contains what
• ❌ Repetitive: Same documents read multiple times across sessions

With DevRag:

• ✅ 40x Less Tokens: Vector search retrieves only relevant chunks (~200 tokens)
• ✅ 15x Faster: Search in 100ms vs 30 seconds of reading
• ✅ Auto-Discovery: Claude Code finds documents without knowing file names

Features

• 🤖 Simple RAG - Retrieval-Augmented Generation for Claude Code
• 📝 Markdown Support - Auto-indexes .md files
• 🔍 Semantic Search - Natural language queries like “JWT authentication method”
• 🚀 Single Binary - No Python, models auto-download on first run
• 💻 CLI & MCP - Use as MCP server or standalone CLI commands
• 🖥️ Cross-Platform - macOS / Linux / Windows
• ⚡ Fast - Auto GPU/CPU detection, incremental sync
• 🌐 Multilingual - Supports 100+ languages including Japanese & English

Quick Start

1. Download Binary

Get the appropriate binary from Releases:

macOS/Linux:

tar -xzf devrag-*.tar.gz
chmod +x devrag-*
sudo mv devrag-* /usr/local/bin/

Note: macOS releases include libonnxruntime.dylib for CoreML GPU acceleration. Keep it in the same directory as the devrag binary.

Windows:

• Extract the zip file
• Place in your preferred location (e.g., C:\Program Files\devrag\)

2. Configure Claude Code

Add to ~/.claude.json or .mcp.json:

{
  "mcpServers": {
    "devrag": {
      "type": "stdio",
      "command": "/usr/local/bin/devrag"
    }
  }
}

Using a custom config file:

{
  "mcpServers": {
    "devrag": {
      "type": "stdio",
      "command": "/usr/local/bin/devrag",
      "args": ["--config", "/path/to/custom-config.json"]
    }
  }
}

3. Add Your Documents

mkdir documents
cp your-notes.md documents/

That’s it! Documents are automatically indexed on startup.

4. Search with Claude Code

In Claude Code:

"Search for JWT authentication methods"

Configuration

Create config.json:

{
  "document_patterns": [
    "./documents",