code-context-mcp


An MCP (Model Context Protocol) server that provides semantic code search capabilities to AI assistants using MongoDB Atlas Vector Search and Voyage AI embeddings.

🚀 Features

- Semantic Code Search: Find relevant code based on meaning, not just keywords
- MongoDB Atlas Vector Search: Unified platform for vectors and data
- Voyage AI Embeddings: State-of-the-art code embeddings (MongoDB exclusive)
- Native Hybrid Search: Combine vector and text search with MongoDB's $rankFusion
- Real-time Sync: Automatic updates with MongoDB Change Streams
- Multi-language Support: TypeScript, JavaScript, Python, Java, Go, Rust, C++

📋 Prerequisites

1. MongoDB Atlas Account (Free tier available)
- Sign up at: https://www.mongodb.com/cloud/atlas/register
- Create a cluster and get your connection string

2. Voyage AI API Key (200M tokens free)
- Sign up at: https://dash.voyageai.com/
- Get your API key

🔧 Installation

$3

``bash


Install globally

npm install -g code-context-mcp

Or use npx (recommended)

npx code-context-mcp
`

$3

Add to your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

`json
{
"mcpServers": {
"code-context": {
"command": "npx",
"args": ["code-context-mcp"],
"env": {
"MONGODB_URI": "mongodb+srv://username:password@cluster.mongodb.net/",
"VOYAGE_API_KEY": "va_xxx"
}
}
}
}
`

$3

#### Cursor

Add to ~/.cursor/mcp.json:

`json
{
"mcpServers": {
"code-context": {
"command": "npx",
"args": ["code-context-mcp"],
"env": {
"MONGODB_URI": "mongodb+srv://...",
"VOYAGE_API_KEY": "va_xxx"
}
}
}
}
`

#### Windsurf

Add to your Windsurf configuration:

`json
{
"mcpServers": {
"code-context": {
"command": "npx",
"args": ["code-context-mcp"],
"env": {
"MONGODB_URI": "mongodb+srv://...",
"VOYAGE_API_KEY": "va_xxx"
}
}
}
}
`

🛠️ Available Tools

The MCP server provides the following tools to AI assistants:

$3

Index a codebase for semantic search.

`typescript
{
"path": "/path/to/project",
"name": "my-project"
}
`

$3

Search for code semantically.

`typescript
{
"projectPath": "/path/to/project",
"query": "authentication middleware",
"limit": 10,
"threshold": 0.7
}
`

$3

Retrieve specific file content.

`typescript
{
"projectPath": "/path/to/project",
"relativePath": "src/auth.ts",
"startLine": 10,
"endLine": 50
}
`

$3

List all indexed projects.

$3

Clear the index for a project.

`typescript
{
"projectPath": "/path/to/project"
}
`

$3

Get statistics about an indexed project.

`typescript
{
"projectPath": "/path/to/project"
}
`

⚙️ Configuration

$3

| Variable | Description | Required | Default |
|----------|-------------|----------|---------|
| MONGODB_URI | MongoDB Atlas connection string | ✅ | - |
| VOYAGE_API_KEY | Voyage AI API key | ✅ | - |
| MONGODB_DATABASE | Database name | ❌ | code_context |
| MONGODB_COLLECTION | Collection name | ❌ | embeddings |
| VOYAGE_MODEL | Voyage AI model | ❌ | voyage-3.5 |
| BATCH_SIZE | Embedding batch size | ❌ | 10 |
| MAX_FILE_SIZE | Max file size (MB) | ❌ | 10 |

$3

| Model | Best For | Performance |
|-------|----------|-------------|
| voyage-context-3 | RAG systems, long documents | +14.24% vs OpenAI |
| voyage-3-large | Highest accuracy | +9.74% vs OpenAI |
| voyage-3.5 | General purpose (default) | +8.26% vs OpenAI |
| voyage-3.5-lite | High throughput | +6.34% vs OpenAI |
| voyage-code-3 | Source code | Best for code |

🏗️ MongoDB Atlas Setup

$3

In MongoDB Atlas:

1. Navigate to your cluster
2. Click "Search" → "Create Search Index"
3. Choose "Atlas Vector Search"
4. Use this configuration:

`json
{
"fields": [{
"type": "vector",
"path": "embedding",
"numDimensions": 1024,
"similarity": "cosine"
}]
}
`

$3

For MongoDB 8.0+, create both vector and text indexes:

`json
{
"mappings": {
"fields": {
"embedding": {
"type": "knnVector",
"dimensions": 1024,
"similarity": "cosine"
},
"content": {
"type": "string",
"analyzer": "lucene.standard"
}
}
}
}
`

📊 Performance

Based on 2025 benchmarks:

- Storage: 83% less than competitors with int8 quantization
- Accuracy: Up to 14.24% better retrieval than OpenAI
- Speed: Native hybrid search 30% faster
- Cost: 96% storage reduction with binary quantization

🔍 Example Usage in Claude

Once configured, you can use natural language commands:

`
"Index my TypeScript project at /Users/me/my-project"

"Search for authentication middleware in my-project"

"Show me the implementation of the UserService class"

"Find all database connection code"

"What files handle error logging?"
`

🐛 Troubleshooting

$3

1. MongoDB Connection Failed
- Verify your connection string
- Check IP whitelist in Atlas
- Ensure cluster is running

2. Voyage AI Authentication Failed
- Verify API key is correct
- Check API key has credits

3. MCP Not Responding
- Check logs in stderr
- Verify environment variables
- Restart AI assistant

$3

Set DEBUG=true in environment variables for verbose logging:

`json
{
"env": {
"DEBUG": "true",
"MONGODB_URI": "...",
"VOYAGE_API_KEY": "..."
}
}
``

🤝 Contributing

Contributions are welcome! Please see our Contributing Guide.

📄 License

MIT License - see LICENSE for details.

🔗 Links

- GitHub Repository
- MongoDB Atlas
- Voyage AI
- Model Context Protocol

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Built with 💚 by MongoDB and Voyage AI