Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.

• 🧠 Your Entire Codebase as Context: Unlike traditional keyword matching that can easily miss relevant code, it uses semantic search to retrieve all your care about from millions of lines of code, without going through multiple hops of discovery, and add to LLM context.
• 💰 Don’t go bankrupt working with large codebase: Compared to simply stuffing a whole directory of files in LLM context for each call, efficient indexing and search in vector database avoids breaking your budget.

Model Context Protocol (MCP) allows you to integrate Claude Context with your favorite AI coding assistants, e.g. Claude Code.

Use the command line interface to add the Claude Context MCP server:

# Add the Claude Context MCP server
claude mcp add claude-context -e OPENAI_API_KEY=your-openai-api-key -e MILVUS_TOKEN=your-zilliz-cloud-api-key -- npx @zilliz/claude-context-mcp@latest

See the Claude Code MCP documentation for more details about MCP server management.

Gemini CLI requires manual configuration through a JSON file:

1. Create or edit the ~/.gemini/settings.json file.
2. Add the following configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

1. Save the file and restart Gemini CLI to apply the changes.

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

"augment.advanced": { 
  "mcpServers": [ 
    { 
      "name": "claude-context", 
      "command": "npx", 
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  ]
}

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

npx @zilliz/claude-context-mcp@latest

For more detailed MCP environment variable configuration, see our Environment Variables Guide.

📚 Need more help? Check out our complete documentation for detailed guides and troubleshooting tips.

• 🔍 Semantic Code Search: Ask questions like "find functions that handle user authentication" and get relevant, context-rich code instantly.
• 🧠 Context-Aware: Discover large codebase, understand how different parts of your codebase relate, even across millions of lines of code.
• ⚡ Incremental Indexing: Efficiently re-index only changed files using Merkle trees.
• 🧩 Intelligent Code Chunking: Analyze code in Abstract Syntax Trees (AST) for chunking.
• 🗄️ Scalable: Integrates with Zilliz Cloud for scalable vector search, no matter how large your codebase is.
• 🛠️ Customizable: Configure file extensions, ignore patterns, and embedding models.

Claude Context is a monorepo containing three main packages:

• @zilliz/claude-context-core: Core indexing engine with embedding and vector database integration
• VSCode Extension: Semantic Code Search extension for Visual Studio Code
• @zilliz/claude-context-mcp: Model Context Protocol server for AI agent integration

• Embedding Providers: OpenAI, VoyageAI, Ollama, Gemini
• Vector Databases: Milvus or Zilliz Cloud(fully managed vector database as a service)
• Code Splitters: AST-based splitter (with automatic fallback), LangChain character-based splitter
• Languages: TypeScript, JavaScript, Python, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, Scala, Markdown
• Development Tools: VSCode, Model Context Protocol

While MCP is the recommended way to use Claude Context with AI assistants, you can also use it directly or through the VSCode extension.

The @zilliz/claude-context-core package provides the fundamental functionality for code indexing and semantic search.

import { Context, MilvusVectorDatabase, OpenAIEmbedding } from '@zilliz/claude-context-core';

// Initialize embedding provider
const embedding = new OpenAIEmbedding({
    apiKey: process.env.OPENAI_API_KEY || 'your-openai-api-key',
    model: 'text-embedding-3-small'
});

// Initialize vector database
const vectorDatabase = new MilvusVectorDatabase({
    address: process.env.MILVUS_ADDRESS || 'your-zilliz-cloud-public-endpoint',
    token: process.env.MILVUS_TOKEN || 'your-zilliz-cloud-api-key'
});

// Create context instance
const context = new Context({
    embedding,
    vectorDatabase
});

// Index your codebase with progress tracking
const stats = await context.indexCodebase('./your-project', (progress) => {
    console.log(`${progress.phase} - ${progress.percentage}%`);
});
console.log(`Indexed ${stats.indexedFiles} files, ${stats.totalChunks} chunks`);

// Perform semantic search
const results = await context.semanticSearch('./your-project', 'vector database operations', 5);
results.forEach(result => {
    console.log(`File: ${result.relativePath}:${result.startLine}-${result.endLine}`);
    console.log(`Score: ${(result.score * 100).toFixed(2)}%`);
    console.log(`Content: ${result.content.substring(0, 100)}...`);
});

Integrates Claude Context directly into your IDE. Provides an intuitive interface for semantic code search and navigation.

1. Direct Link: Install from VS Code Marketplace
2. Manual Search:
   • Open Extensions view in VSCode (Ctrl+Shift+X or Cmd+Shift+X on Mac)
   • Search for "Semantic Code Search"
   • Click Install

# Clone repository
git clone https://github.com/zilliztech/claude-context.git
cd claude-context

# Install dependencies
pnpm install

# Build all packages
pnpm build

# Start development mode
pnpm dev

# Build all packages
pnpm build

# Build specific package
pnpm build:core
pnpm build:vscode
pnpm build:mcp

# Development with file watching
cd examples/basic-usage
pnpm dev

By default, Claude Context supports:

• Programming languages: .ts, .tsx, .js, .jsx, .py, .java, .cpp, .c, .h, .hpp, .cs, .go, .rs, .php, .rb, .swift, .kt, .scala, .m, .mm
• Documentation: .md, .markdown, .ipynb

Common directories and files are automatically ignored:

• Build outputs: node_modules/**, dist/**, build/**, out/**, target/**, coverage/**, .nyc_output/**
• Version control: .git/**, .svn/**, .hg/**
• IDE/Editor files: .vscode/**, .idea/**, *.swp, *.swo
• Cache directories: .cache/**, __pycache__/**, .pytest_cache/**
• Logs and temporary: logs/**, tmp/**, temp/**, *.log
• Environment files: .env, .env.*, *.local
• Minified/bundled files: *.min.js, *.min.css, *.bundle.js, *.bundle.css, *.chunk.js, *.map

See FAQ Guide for detailed and customized configuration of supported file extensions and ignore patterns.

Check the /examples directory for complete usage examples:

• Basic Usage: Simple indexing and search example

For frequently asked questions and troubleshooting tips, see our FAQ Guide.

We welcome contributions! Please see our Contributing Guide for details on how to get started.

Package-specific contributing guides:

• Core Package Contributing
• MCP Server Contributing
• VSCode Extension Contributing

• AST-based code analysis for improved understanding
• Support for additional embedding providers
• Agent-based interactive search mode
• Enhanced code chunking strategies
• Search result ranking optimization
• Robust Chrome Extension

This project is licensed under the MIT License - see the LICENSE file for details.

• GitHub Repository
• VSCode Marketplace
• Milvus Documentation
• Zilliz Cloud