code-context

Your entire codebase as Claude's context

Note: This project is a fork of Code Context: https://github.com/zilliztech/code-context to replace the milvus vector database to sqlite

Code 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: Code Context uses semantic search to find all relevant code from millions of lines. No multi-round discovery needed. It brings results straight into the Claude's context.

💰 Cost-Effective for Large Codebases: Instead of loading entire directories into Claude for every request, which can be very expensive, Code Context efficiently stores your codebase in a vector database and only uses related code in context to keep your costs manageable.

Quick Start

Prerequisites

Configure MCP for Claude Code

System Requirements:

• Node.js >= 20.0.0 and < 24.0.0

Code Context is not compatible with Node.js 24.0.0, you need downgrade it first if your node version is greater or equal to 24.

Configuration

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

claude mcp add code-context \
  -e OPENAI_API_KEY=sk-your-openai-api-key \
  -- npx @tan-yong-sheng/code-context-mcp@latest

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

Other MCP Client Configurations

# IMPORTANT: the top-level key is `mcp_servers` rather than `mcpServers`.
[mcp_servers.code-context]
command = "npx"
args = ["@tan-yong-sheng/code-context-mcp@latest"]
env = { "OPENAI_API_KEY" = "your-openai-api-key" }
# Optional: override the default 10s startup timeout
startup_timeout_ms = 20000

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

"augment.advanced": {
  "mcpServers": [
    {
      "name": "code-context",
      "command": "npx",
      "args": ["-y", "@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  ]
}

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["@tan-yong-sheng/code-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key"
      }
    }
  }
}

{
    "command": "npx",
    "args": ["@tan-yong-sheng/code-context-mcp@latest"],
    "env": {
      "OPENAI_API_KEY": "your-openai-api-key"
    }
}

npx @tan-yong-sheng/code-context-mcp@latest

Usage in Your Codebase

1. Open Claude Code

   cd your-project-directory
   claude
   

2. Index your codebase:

   Index this codebase
   

3. Check indexing status:

   Check the indexing status
   

4. Start searching:

   Find functions that handle user authentication
   

🎉 That's it! You now have semantic code search in Claude Code.

Environment Variables Configuration

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

Using Different Embedding Models

To configure custom embedding models (e.g., text-embedding-3-large for OpenAI, voyage-code-3 for VoyageAI), see the MCP Configuration Examples for detailed setup instructions for each provider.

File Inclusion & Exclusion Rules

For detailed explanation of file inclusion and exclusion rules, and how to customize them, see our File Inclusion & Exclusion Rules.

Available Tools

1. index_codebase

Index a codebase directory for hybrid search (BM25 + dense vector).

2. search_code

Search the indexed codebase using natural language queries with hybrid search (BM25 + dense vector).

3. clear_index

Clear the search index for a specific codebase.

4. get_indexing_status

Get the current indexing status of a codebase. Shows progress percentage for actively indexing codebases and completion status for indexed codebases.

🏗️ Architecture

🔧 Implementation Details

• 🔍 Hybrid Code Search: Ask questions like "find functions that handle user authentication" and get relevant, context-rich code instantly using advanced hybrid search (BM25 + dense vector).
• 🧠 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.
• 🗄️ Local-First: Uses sqlite-vec for local vector storage - no external database needed, works offline.
• 🛠️ Customizable: Configure file extensions, ignore patterns, and embedding models.

Core Components

Code Context is a monorepo containing two main packages:

• @tan-yong-sheng/code-context-core: Core indexing engine with embedding and vector database integration
• @tan-yong-sheng/code-context-mcp: Model Context Protocol server for AI agent integration

And it also has a VSCode extension here: https://marketplace.visualstudio.com/items?itemName=tan-yong-sheng.ai-code-context

Supported Technologies

• Embedding Providers: OpenAI, VoyageAI, Ollama, Gemini
• Vector Database: sqlite-vec (local SQLite-based vector database - zero config!)
• 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

📦 Other Ways to Use Code Context

While MCP is the recommended way to use Code Context with AI assistants, you can also use it directly via the Core Package.

Build Applications with Core Package

The @tan-yong-sheng/code-context-core package provides the fundamental functionality for code indexing and semantic search.

import { Context, SqliteVecVectorDatabase, OpenAIEmbedding } from '@tan-yong-sheng/code-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 (sqlite-vec - zero config!)
const vectorDatabase = new SqliteVecVectorDatabase();

// 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)}...`);
});

🛠️ Development

Setup Development Environment

Prerequisites

• Node.js 20.x or 22.x
• pnpm (recommended package manager)

Cross-Platform Setup

# Clone repository
git clone https://github.com/tan-yong-sheng/code-context.git
cd code-context

# Install dependencies
pnpm install

# Build all packages
pnpm build

# Start development mode
pnpm dev

Windows-Specific Setup

On Windows, ensure you have:

• Git for Windows with proper line ending configuration
• Node.js installed via the official installer or package manager
• pnpm installed globally: npm install -g pnpm

# Windows PowerShell/Command Prompt
git clone https://github.com/tan-yong-sheng/code-context.git
cd code-context

# Configure git line endings (recommended)
git config core.autocrlf false

# Install dependencies
pnpm install

# Build all packages (uses cross-platform scripts)
pnpm build

# Start development mode
pnpm dev

Building

# Build all packages (cross-platform)
pnpm build

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

# Performance benchmarking
pnpm benchmark

Windows Build Notes

• All build scripts are cross-platform compatible using rimraf
• Build caching is enabled for faster subsequent builds
• Use PowerShell or Command Prompt - both work equally well

Running Examples

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

📖 Examples

Check the /examples directory for complete usage examples:

• Basic Usage: Simple indexing and search example

❓ FAQ

Common Questions:

• What files does Code Context decide to embed?
• Can I use a fully local deployment setup?
• Does it support multiple projects / codebases?
• How does Code Context compare to other coding tools?

❓ For detailed answers and more troubleshooting tips, see our FAQ Guide.

🔧 Encountering issues? Visit our Troubleshooting Guide for step-by-step solutions.

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

🤝 Contributing

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

🗺️ Roadmap

• 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

📄 License

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

🔗 Links

• GitHub Repository
• sqlite-vec - SQLite extension for vector search