MongoDB That Works

A reliable MongoDB MCP (Model Context Protocol) server that provides seamless MongoDB integration for Claude Desktop with built-in schema discovery and field validation.

- 🔍Schema Discovery: Automatically analyze collection structures
- ✅Field Validation: Prevent field name mistakes
- 📊Full MongoDB Support: Find, aggregate, insert, update, delete operations
- 🚀High Performance: Efficient connection pooling and query optimization
- 🔐Secure: Support for MongoDB Atlas and authentication
- 🎯Type-Safe: Built with TypeScript and Zod validation

npm install -g @sourabhshegane/mongodb-mcp-that-works

Add to your Claude Desktop configuration file:

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

{ "mcpServers": { "mongodb": { "command": "npx", "args": ["-y", "@sourabhshegane/mongodb-mcp-that-works@latest"], "env": { "MONGODB_URI": "mongodb+srv://username:password@cluster.mongodb.net/database", "MONGODB_DATABASE": "your_database_name" } } } }

- MONGODB_URI: Your MongoDB connection string (required)
- MONGODB_DATABASE: Default database name (optional)

// Example mcp.listCollections({ filter: {} })

Find documents in a collection with filtering, sorting, and pagination.

// Example mcp.find({ collection: "users", filter: { status: "active" }, sort: { createdAt: -1 }, limit: 10 })

// Example mcp.findOne({ collection: "users", filter: { email: "user@example.com" } })

// Example mcp.aggregate({ collection: "orders", pipeline: [ { $match: { status: "completed" } }, { $group: { _id: "$userId", total: { $sum: "$amount" } } } ] })

// Example mcp.count({ collection: "products", filter: { inStock: true } })

// Example mcp.distinct({ collection: "orders", field: "status" })

// Example mcp.insertOne({ collection: "users", document: { name: "John Doe", email: "john@example.com" } })

// Example mcp.updateOne({ collection: "users", filter: { _id: "123" }, update: { $set: { status: "active" } } })

// Example mcp.deleteOne({ collection: "users", filter: { _id: "123" } })

Analyze collection structure and discover field names.

// Example mcp.getSchema({ collection: "users", sampleSize: 100 }) // Returns: { "collection": "users", "sampleSize": 100, "fields": { "_id": { "types": ["ObjectId"], "examples": ["507f1f77bcf86cd799439011"], "frequency": "100/100", "percentage": 100 }, "email": { "types": ["string"], "examples": ["user@example.com"], "frequency": "100/100", "percentage": 100 } } }

- Use Schema Discovery First: Before querying, rungetSchemato understand field names
- Handle ObjectIds: The server automatically converts string IDs to ObjectIds
- Use Projections: Limit returned fields to improve performance
- Batch Operations: Use aggregation pipelines for complex queries

// Get schema first to avoid field name mistakes const schema = await mcp.getSchema({ collection: "reports" }); // Use correct field names from schema const reports = await mcp.find({ collection: "reports", filter: { organization_id: "64ba7374f8b63db2083b2665" }, limit: 10 });

const analytics = await mcp.aggregate({ collection: "orders", pipeline: [ { $match: { createdAt: { $gte: new Date("2024-01-01") } } }, { $group: { _id: { $dateToString: { format: "%Y-%m", date: "$createdAt" } }, revenue: { $sum: "$amount" }, count: { $sum: 1 } }}, { $sort: { _id: 1 } } ] });

- Verify your MongoDB URI is correct
- Check network connectivity to MongoDB Atlas
- Ensure IP whitelist includes your current IP

- Always usegetSchemato discover correct field names
- Remember MongoDB is case-sensitive
- Check for typos in nested field paths (e.g., "user.profile.name")

- Use indexes for frequently queried fields
- Limit result sets withlimitparameter
- Use projections to return only needed fields

MIT License - see LICENSE file for details

- Initial release
- Full MongoDB CRUD operations
- Schema discovery tool
- Automatic ObjectId conversion
- TypeScript support

Made out of pain since the official MongoDB MCP didn't work for me

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