MongoDB MCP

MongoDB MCP

A MongoDB MCP Server that allows AI agents and MCP clients to interact with MongoDB databases through standardized tools for CRUD operations, schema discovery, and collection management.

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MongoDB MCP

A MongoDB Model Context Protocol (MCP) Server that allows AI agents and MCP clients to interact with MongoDB databases through standardized tools.

Features

  • List all collections
  • Discover collection schemas
  • Fetch collection data
  • Query documents
  • Insert documents
  • Update documents
  • Delete documents
  • MongoDB Atlas support
  • Local MongoDB support
  • MCP stdio transport support

Installation

Using pip

pip install mongo-mcp

Using uv

uv add mongo-mcp

Prerequisites

  • Python 3.10+
  • MongoDB Local Instance or MongoDB Atlas Cluster

Examples:

mongodb://localhost:27017

or

mongodb+srv://username:password@cluster.mongodb.net

Configuration

MongoDB MCP uses environment variables to connect to your database.

Create a .env file:

MONGODB_URI=mongodb://localhost:27017
DATABASE_NAME=shipbihar

Environment Variables

Variable Description Required
MONGODB_URI MongoDB connection string Yes
DATABASE_NAME Database name Yes

Running the MCP Server

mongo_mcp

or

python -m mongo_mcp.main

The MCP server will start using stdio transport.


MCP Client Configuration

Example MCP configuration:

{
  "mcpServers": {
    "mongodb": {
      "command": "mongo_mcp",
      "env": {
        "MONGODB_URI": "mongodb://localhost:27017",
        "DATABASE_NAME": "shipbihar"
      }
    }
  }
}

Available Tools

all_collections

Returns all collections in the configured database.

Example Output:

[
  "users",
  "orders",
  "shipments"
]

fetch_collection_schema

Returns an inferred schema from a sample document.

Example:

{
  "_id": "ObjectId",
  "name": "str",
  "email": "str",
  "createdAt": "datetime"
}

fetch_collection_data

Returns documents from a collection.

Parameters:

{
  "collection_name": "users",
  "limit": 100
}

find_document

Find a document using a MongoDB query.

Example:

{
  "collection_name": "users",
  "query": {
    "email": "john@example.com"
  }
}

insert_document

Insert a document.

Example:

{
  "collection_name": "users",
  "document": {
    "name": "John",
    "email": "john@example.com"
  }
}

update_document

Update matching documents.

Example:

{
  "collection_name": "users",
  "filter_query": {
    "email": "john@example.com"
  },
  "update_data": {
    "role": "admin"
  }
}

delete_document

Delete matching documents.

Example:

{
  "collection_name": "users",
  "filter_query": {
    "email": "john@example.com"
  }
}

Common Errors

Error: DATABASE_NAME is None

Error:

TypeError: name must be an instance of str, not <class 'NoneType'>

Reason:

MongoDB MCP cannot find the DATABASE_NAME environment variable.

Solution:

Create a .env file:

MONGODB_URI=mongodb://localhost:27017
DATABASE_NAME=your_database_name

or export variables manually.

Windows PowerShell:

$env:MONGODB_URI="mongodb://localhost:27017"
$env:DATABASE_NAME="shipbihar"

Linux/macOS:

export MONGODB_URI="mongodb://localhost:27017"
export DATABASE_NAME="shipbihar"

Error: Connection Refused

Error:

ServerSelectionTimeoutError

Reason:

MongoDB server is not running.

Solution:

Start MongoDB:

mongod

or verify your Atlas connection string.


Error: Authentication Failed

Error:

Authentication failed

Reason:

Incorrect username or password.

Solution:

Verify your MongoDB credentials.


Security

Recommended:

  • Use dedicated database users
  • Restrict permissions when possible
  • Avoid connecting with admin credentials
  • Store secrets in environment variables

Do NOT:

  • Commit .env files to GitHub
  • Hardcode MongoDB passwords in code

Development

Clone the repository:

git clone <repository-url>
cd mongo-mcp

Create environment:

uv venv
source .venv/bin/activate

Install dependencies:

uv sync

Run locally:

python -m mongo_mcp.main

Roadmap

V1

  • Collection discovery
  • CRUD operations
  • Schema inspection

V2

  • Aggregation pipelines
  • Count documents
  • Regex search

V3

  • Natural language queries
  • Query optimization
  • Schema caching

License

MIT License


Author

Vishnu Bhardwaj

Built for AI Agents, MCP Clients, and MongoDB Developers.

mongo_agent_mcp

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