What is Mcp Mongodb

The mcp_mongodb is a MongoDB MCP Server that provides a natural language interface for agentic applications, allowing users to efficiently manage and search data in MongoDB.

Use cases

Use cases include storing documents, creating indexes, finding documents based on criteria, and performing complex data processing with aggregation pipelines.

How to use

To use mcp_mongodb, clone the repository, install dependencies, and configure environment variables. You can then interact with MongoDB using natural language queries through MCP clients.

Key features

Key features include natural language queries, seamless MCP integration, full MongoDB support (collections, documents, indexes, aggregations), efficient search and filtering, and a scalable, lightweight design.

Where to use

mcp_mongodb can be used in various fields such as data management, AI-driven applications, and any environment where efficient data querying and manipulation in MongoDB is required.

MongoDB MCP Server

Overview

The MongoDB MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in MongoDB. It integrates seamlessly with MCP (Model Content Protocol) clients, enabling AI-driven workflows to interact with structured and unstructured data in MongoDB. Using this MCP Server, you can ask questions like:

• “Store this document in the collection”
• “Create an index on this field”
• “Find documents matching these criteria”
• “Perform an aggregation pipeline”

Features

• Natural Language Queries: Enables AI agents to query and update MongoDB using natural language.
• Seamless MCP Integration: Works with any MCP client for smooth communication.
• Full MongoDB Support: Handles collections, documents, indexes, and aggregations.
• Search & Filtering: Supports efficient data retrieval and querying in MongoDB.
• Scalable & Lightweight: Designed for high-performance data operations.

Tools

This MCP Server provides tools to manage the data stored in MongoDB.

• collection tools to create, drop and list collections
• document tools to insert, update, delete and query documents
• index tools to create and manage indexes for efficient querying
• aggregation tools to perform complex data processing pipelines
• query tools to find and filter documents with various conditions

Installation

Manual Installation

# Clone the repository
git clone [https://github.com/mongodb/mcp-mongodb.git](https://github.com/tkz24589/mcp_mongodb)
cd mcp-mongodb

# Install dependencies using uv
uv venv
source .venv/bin/activate
uv sync

Configuration

To configure this MongoDB MCP Server, consider the following environment variables:

Integration with Claude Desktop

You can configure Claude Desktop to use this MCP Server.

1. Specify your MongoDB credentials and TLS configuration
2. Retrieve your uv command full path (e.g. which uv)
3. Edit the claude_desktop_config.json configuration file
   • on a MacOS, at ~/Library/Application\ Support/Claude/

{
    "mcpServers": {
        "mongodb": {
            "command": "<full_path_uv_command>",
            "args": [
                "--directory",
                "<your_mcp_server_directory>",
                "run",
                "src/main.py"
            ],
            "env": {
                "MONGODB_HOST": "<your_mongodb_host>",
                "MONGODB_PORT": "<your_mongodb_port>",
                "MONGODB_USERNAME": "<your_mongodb_username>",
                "MONGODB_PASSWORD": "<your_mongodb_password>",
                "MONGODB_AUTH_SOURCE": "<your_auth_source>",
                "MONGODB_SSL": True|False,
                "MONGODB_CA_PATH": "<your_mongodb_ca_path>"
            }
        }
    }
}

You can troubleshoot problems by tailing the log file.

tail -f ~/Library/Logs/Claude/mcp-server-mongodb.log

Docker

docker compose up -d

Example Use Cases

• AI Assistants: Enable LLMs to fetch, store, and process data in MongoDB.
• Chatbots & Virtual Agents: Retrieve document data, manage collections, and personalize responses.
• Data Search & Analytics: Query MongoDB for real-time insights and complex aggregations.
• Document Processing: Manage document collections with flexible schema and indexing.

Contributing

1. Fork the repo
2. Create a new branch (feature-branch)
3. Commit your changes
4. Push to your branch and submit a PR!

License

This project is licensed under the MIT License.

Contact

For questions or support, reach out via GitHub Issues.