Mongodb Mcp Server

MongoDB MCP Server

A Model Context Protocol server for interacting with MongoDB Databases and MongoDB Atlas.

Quick Start

Using the official MongoDB plugins for AI agents

MongoDB MCP Server comes bundled with the official MongoDB plugins for AI agents. The following plugins are available:

mongodb-atlas — connects to the MongoDB-hosted Atlas MCP server over OAuth. This does not require you to run anything locally, and is the recommended way to connect to MongoDB Atlas from your AI agent:

• Cursor: marketplace
• VSCode: Open the Extensions view (⇧⌘X / Ctrl+Shift+X), search for @agentPlugins, and install mongodb-atlas.
• Claude: marketplace
• Codex: Open /plugins and install mongodb-atlas.
• GitHub Copilot CLI: Run copilot plugin install mongodb-atlas.
• Grok: Open /marketplace in Grok Build and install mongodb-atlas.

mongodb — runs the MongoDB MCP server locally and connects to any self-managed deployment:

• Cursor: marketplace
• Claude: marketplace
• Gemini: marketplace
• Codex: Run codex plugin marketplace add mongodb/agent-skills, then open /plugins and install mongodb.
• GitHub Copilot CLI: Run copilot plugin install mongodb.
• Grok: Open /marketplace in Grok Build and install mongodb.

Using the setup script

You can manually set up the local MCP server by running the following command:

npx -y mongodb-mcp-server@latest setup

This will guide you through an interactive setup process, including configuring your MongoDB connection string or Atlas API credentials.

For more advanced setup options, see the Manual Setup section below.

Using the MongoDB MCP Server setup skill

You can add and use the MongoDB MCP Server setup skill to configure your local MCP server using an AI agent.

npx skills add https://github.com/mongodb/agent-skills --skill mongodb-mcp-setup

Using manual configuration

See Manual Setup for instructions on how to manually configure the MongoDB MCP Server.

📚 Table of Contents

• 🚀 Getting Started
  • Prerequisites
  • Manual Setup
• 🛠️ Supported Tools
  • MongoDB Atlas Tools
  • MongoDB Database Tools
  • MongoDB Assistant Tools
• 📄 Supported Resources
• ⚙️ Configuration
  • Configuration Options
  • Atlas API Access
  • Configuration Methods
    • Environment Variables
    • Command-Line Arguments
    • MCP Client Configuration
    • Proxy Support
• 🚀 Deploy on Public Clouds
  • Azure Cloud
• 🤝 Contributing

Prerequisites

[!NOTE] Node 20.x support is deprecated and will be removed in a future release. Please upgrade to Node 22.13 or later. See https://nodejs.org/en/blog/migrations/v20-to-v22 for migration details.

• Node.js

  • At least v22.13.0. Check with node -v.

• A MongoDB connection string or Atlas API credentials.

  • Service Accounts Atlas API credentials are required to use the Atlas tools. You can create a service account in MongoDB Atlas and use its credentials for authentication. See Atlas API Access for more details.
  • If you have a MongoDB connection string, you can use it directly to connect to your MongoDB instance.

Manual Setup

🔒 Security Recommendation 1: When using Atlas API credentials, be sure to assign only the minimum required permissions to your service account. See Atlas API Permissions for details.

🔒 Security Recommendation 2: For enhanced security, we strongly recommend using environment variables to pass sensitive configuration such as connection strings and API credentials instead of command line arguments. Command line arguments can be visible in process lists and logged in various system locations, potentially exposing your secrets. Environment variables provide a more secure way to handle sensitive information.

Most MCP clients require a configuration file to be created or modified to add the MCP server.

Note: The configuration file syntax can be different across clients. Please refer to the following links for the latest expected syntax:

• Devin AI
• Claude Desktop & Web
• Cursor
• Codex
• Other AI clients

Default Safety Notice: All examples below include --readOnly by default to ensure safe, read-only access to your data. Remove --readOnly if you need to enable write operations.

Option 1: Connection String

You can pass your connection string via environment variables, make sure to use a valid username and password.

{
  "mcpServers": {
    "MongoDB": {
      "command": "npx",
      "args": ["-y", "mongodb-mcp-server@latest", "--readOnly"],
      "env": {
        "MDB_MCP_CONNECTION_STRING": "mongodb://localhost:27017/myDatabase"
      }
    }
  }
}

NOTE: The connection string can be configured to connect to any MongoDB cluster, whether it's a local instance or an Atlas cluster.

Option 2: Connect to the MongoDB Atlas-Managed MCP Server

When working with MongoDB Atlas, the recommended approach is to install the mongodb-atlas plugin for your AI agent, which handles OAuth authentication automatically.

For manual configuration, see the client-specific instructions for setting up the Atlas Remote MCP server with OAuth. Alternatively, you can connect using the mongodb-atlas-mcp-remote package with Service Account credentials — see the package README for setup instructions.

Note: You cannot authenticate to the remote MongoDB MCP server using a static API key over HTTP. You must either:

• Use a client that supports the OAuth flow.
• Use the mongodb-atlas-mcp-remote stdio server, which you can authenticate into using the static MDB_MCP_API_CLIENT_ID and MDB_MCP_API_CLIENT_SECRET environment variables.

To connect with the mongodb-atlas-mcp-remote stdio server using Service Account credentials, add it to your client's MCP configuration:

{
  "mcpServers": {
    "mongodb-atlas-mcp-remote": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "mongodb-atlas-mcp-remote@latest"],
      "env": {
        "MDB_MCP_API_CLIENT_ID": "$CLIENT_ID",
        "MDB_MCP_API_CLIENT_SECRET": "$SECRET"
      }
    }
  }
}

Option 3: Atlas API Credentials

Use your Atlas API Service Accounts credentials. Must follow all the steps in Atlas API Access section.

{
  "mcpServers": {
    "MongoDB": {
      "command": "npx",
      "args": ["-y", "mongodb-mcp-server@latest", "--readOnly"],
      "env": {
        "MDB_MCP_API_CLIENT_ID": "your-atlas-service-accounts-client-id",
        "MDB_MCP_API_CLIENT_SECRET": "your-atlas-service-accounts-client-secret"
      }
    }
  }
}

Option 4: Standalone Service using environment variables and command line arguments

You can source environment variables defined in a config file or explicitly set them like we do in the example below and run the server via npx.

# Set your credentials as environment variables first
export MDB_MCP_API_CLIENT_ID="your-atlas-service-accounts-client-id"
export MDB_MCP_API_CLIENT_SECRET="your-atlas-service-accounts-client-secret"

# Then start the server
npx -y mongodb-mcp-server@latest --readOnly

💡 Platform Note: The examples above use Unix/Linux/macOS syntax. For Windows users, see Environment Variables for platform-specific instructions.

• For a complete list of configuration options see Configuration Options
• To configure your Atlas Service Accounts credentials please refer to Atlas API Access
• Connection String via environment variables in the MCP file example
• Atlas API credentials via environment variables in the MCP file example

Option 5: Using Docker

You can run the MongoDB MCP Server in a Docker container, which provides isolation and doesn't require a local Node.js installation.

Run with Environment Variables

You may provide either a MongoDB connection string OR Atlas API credentials:

Option A: No configuration

docker run --rm -i \
  mongodb/mongodb-mcp-server:latest

Option B: With MongoDB connection string

# Set your credentials as environment variables first
export MDB_MCP_CONNECTION_STRING="mongodb+srv://username:password@cluster.mongodb.net/myDatabase"

# Then start the docker container
docker run --rm -i \
  -e MDB_MCP_CONNECTION_STRING \
  -e MDB_MCP_READ_ONLY="true" \
  mongodb/mongodb-mcp-server:latest

💡 Platform Note: The examples above use Unix/Linux/macOS syntax. For Windows users, see Environment Variables for platform-specific instructions.

Option C: With Atlas API credentials

# Set your credentials as environment variables first
export MDB_MCP_API_CLIENT_ID="your-atlas-service-accounts-client-id"
export MDB_MCP_API_CLIENT_SECRET="your-atlas-service-accounts-client-secret"

# Then start the docker container
docker run --rm -i \
  -e MDB_MCP_API_CLIENT_ID \
  -e MDB_MCP_API_CLIENT_SECRET \
  -e MDB_MCP_READ_ONLY="true" \
  mongodb/mongodb-mcp-server:latest

💡 Platform Note: The examples above use Unix/Linux/macOS syntax. For Windows users, see Environment Variables for platform-specific instructions.

Docker in MCP Configuration File

Without options:

{
  "mcpServers": {
    "MongoDB": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-e",
        "MDB_MCP_READ_ONLY=true",
        "-i",
        "mongodb/mongodb-mcp-server:latest"
      ]
    }
  }
}

With connection string:

{
  "mcpServers": {
    "MongoDB": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "MDB_MCP_CONNECTION_STRING",
        "-e",
        "MDB_MCP_READ_ONLY=true",
        "mongodb/mongodb-mcp-server:latest"
      ],
      "env": {
        "MDB_MCP_CONNECTION_STRING": "mongodb+srv://username:password@cluster.mongodb.net/myDatabase"
      }
    }
  }
}

With Atlas API credentials:

{
  "mcpServers": {
    "MongoDB": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "MDB_MCP_READ_ONLY=true",
        "-e",
        "MDB_MCP_API_CLIENT_ID",
        "-e",
        "MDB_MCP_API_CLIENT_SECRET",
        "mongodb/mongodb-mcp-server:latest"
      ],
      "env": {
        "MDB_MCP_API_CLIENT_ID": "your-atlas-service-accounts-client-id",
        "MDB_MCP_API_CLIENT_SECRET": "your-atlas-service-accounts-client-secret"
      }
    }
  }
}

🛠️ Supported Tools

Tool List

MongoDB Database Tools

• aggregate - Run an aggregation against a MongoDB collection
• aggregate-db - Run an aggregation against a MongoDB database
• collection-indexes - Describe the indexes for a collection
• collection-schema - Describe the schema for a collection
• collection-storage-size - Gets the size of the collection
• connect - Connect to a MongoDB instance
• count - Gets the number of documents in a MongoDB collection using db.collection.count() and query as an optional filter parameter
• create-collection - Creates a new collection in a database. If the database doesn't exist, it will be created automatically.
• create-index - Create an index for a collection
• db-stats - Returns statistics that reflect the use state of a single database
• delete-many - Removes all documents that match the filter from a MongoDB collection
• disconnect - Close a MongoDB connection and revoke its connectionId.
• drop-collection - Removes a collection or view from the database. The method also removes any indexes associated with the dropped collection.
• drop-database - Removes the specified database, deleting the associated data files
• drop-index - Drop an index for the provided database and collection.
• explain - Returns statistics describing the execution of the winning plan chosen by the query optimizer for the evaluated method
• export - Export a query or aggregation results in the specified EJSON format.
• find - Run a find query against a MongoDB collection
• insert-many - Insert an array of documents into a MongoDB collection. If the list of documents is above com.mongodb/maxRequestPayloadBytes, consider inserting them in batches.
• list-collections - List all collections for a given database
• list-connections - List the active MongoDB connections and their connectionIds. Use this to find a connectionId established earlier.
• list-databases - List all databases for a MongoDB connection
• mongodb-logs - Returns the most recent logged mongod events
• rename-collection - Renames a collection in a MongoDB database
• update-many - Updates all documents that match the specified filter for a collection. If the list of documents is above com.mongodb/maxRequestPayloadBytes, consider updating them in batches.

MongoDB Atlas Tools

• atlas-connect-cluster - Connect to MongoDB Atlas cluster and get back a connectionId to pass to the other MongoDB tools. Each call establishes a new, independent connection — multiple connections can be active at the same time.
• atlas-create-access-list - Allow Ip/CIDR ranges to access your MongoDB Atlas clusters.
• atlas-create-cluster - Create a MongoDB Atlas cluster (M10–M80, replica set or single shard). Compute autoscaling is enabled by default: min instance size is set to the selected instance size, max is set two tiers above. Disk autoscaling is always enabled. Encryption at rest with customer-managed keys (CMK) is supported, the CMK provider must already have a valid encryption at rest configuration in the project. The tool returns immediately, use the atlas-inspect-cluster tool to poll the cluster state for readiness (state: IDLE). Connection strings are unavailable until the cluster reaches IDLE state.
• atlas-create-db-user - Create an MongoDB Atlas database user
• atlas-create-free-cluster - Create a free MongoDB Atlas cluster
• atlas-create-project - Create a MongoDB Atlas project
• atlas-get-performance-advisor - Get MongoDB Atlas performance advisor recommendations and suggestions, which includes the operations: suggested indexes, drop index suggestions, schema suggestions, and a sample of the most recent (max 50) slow query logs
• atlas-get-regions - List supported MongoDB Atlas regions for a cloud provider.
• atlas-inspect-access-list - Inspect Ip/CIDR ranges with access to your MongoDB Atlas clusters.
• atlas-inspect-cluster - Inspect metadata of a MongoDB Atlas cluster
• atlas-list-alerts - List triggered alerts for a MongoDB Atlas project. These are alerts Atlas has raised, not the alert configurations that define them. Defaults to OPEN alerts; set status to TRACKING or CLOSED to see others.
• atlas-list-clusters - List MongoDB Atlas clusters
• atlas-list-db-users - List MongoDB Atlas database users
• atlas-list-orgs - List MongoDB Atlas organizations
• atlas-list-projects - List MongoDB Atlas projects.
• atlas-load-sample-dataset - Load a MongoDB sample dataset into an Atlas cluster, or check the status of a previously-initiated load. To start a new load, provide clusterName — the load runs asynchronously and the response includes a jobId and initial state. To check progress, call this tool again with jobId (sample dataset loads typically take 1–5 minutes). State can be WORKING, COMPLETED, or FAILED.
• atlas-pause-resume-cluster - Pause or resume a dedicated (M10+) MongoDB Atlas cluster.
• atlas-streams-build - Create Atlas Stream Processing resources. Use this tool for 'set up a Kafka pipeline', 'create a workspace', 'add a connection', or 'deploy a processor'. Use resource='workspace' to create a new workspace (specify cloud provider, region, and tier). Use resource='connection' to add a data source or sink to an existing workspace. Use resource='processor' to deploy a stream processor with a pipeline. Use resource='privatelink' to set up private networking. Typical workflow: create workspace → add connections → deploy processor.
• atlas-streams-discover - Discover and inspect Atlas Stream Processing resources. Also use for 'why is my processor failing', 'what workspaces do I have', 'show processor stats', or 'check processor health'. Use 'list-workspaces' to see all workspaces in a project. Use inspect actions for details on a specific resource. Use 'diagnose-processor' for a combined health report including state, stats, connection health, and recent errors. Use 'get-networking' for PrivateLink and account details.
• atlas-streams-manage - Manage Atlas Stream Processing resources: start/stop processors, modify pipelines, update configurations. Also use for 'change the pipeline', 'scale up my processor', or 'update my workspace tier'. Common workflow: action='stop-processor' → action='modify-processor' → action='start-processor'. Use atlas-streams-discover with action 'inspect-processor' to check state before managing.
• atlas-streams-teardown - Delete Atlas Stream Processing resources. Also use for 'remove my workspace', 'disconnect a source', 'delete all processors', or 'clean up my streams environment'. Performs basic safety checks before deletion: summarizes counts of processors and connections, highlights connections referenced by processors where possible, and surfaces API errors if processors are still running when deletion is attempted. Use atlas-streams-discover to review resources before deleting.
• atlas-upgrade-cluster - Upgrade or scale a MongoDB Atlas cluster. Free and Flex clusters can be upgraded to Flex or M10 Dedicated. Dedicated clusters can be scaled to a different instance size, and compute autoscaling settings can be updated. When scaling a Dedicated cluster, at least one of targetTier, computeAutoScaling, minInstanceSize, or maxInstanceSize must be provided. Compute autoscaling defaults to enabled when upgrading to M10 Dedicated: min instance size is set to the selected instance size, max is set two tiers above, unless overridden. Note to LLM: If provider and region are not already known, ask for both together in a single question before calling this tool. Use atlas-get-regions to resolve natural-language locations or uncertain region codes before calling this tool.

NOTE: atlas tools are only available when you set credentials on configuration section.

MongoDB Atlas Local Tools

• atlas-local-connect-deployment - Connect to a MongoDB Atlas Local deployment and get back a connectionId to pass to the other MongoDB tools
• atlas-local-create-deployment - Create a MongoDB Atlas local deployment. Default image is preview. When the user does not specify an image tag, inform them that preview is used by default and provide this link for more information: https://hub.docker.com/r/mongodb/mongodb-atlas-local
• atlas-local-delete-deployment - Delete a MongoDB Atlas local deployment
• atlas-local-list-deployments - List MongoDB Atlas local deployments

MongoDB Assistant Tools

• list-knowledge-sources - List available data sources in the MongoDB Assistant knowledge base. Use this to explore available data sources or to find search filter parameters to use in search-knowledge.
• search-knowledge - Search for information in the MongoDB Assistant knowledge base. This includes official documentation, curated expert guidance, and other resources provided by MongoDB. Supports filtering by data source and version.

📄 Supported Resources

• config - Server configuration, supplied by the user either as environment variables or as startup arguments with sensitive parameters redacted. The resource can be accessed under URI config://config.
• debug - Debugging information for MongoDB connectivity issues. Tracks the last connectivity attempt and error information. The resource can be accessed under URI debug://mongodb.
• exported-data - A resource template to access the data exported using the export tool. The template can be accessed under URI exported-data://{exportName} where exportName is the unique name for an export generated by the export tool.

Configuration

🔒 Security Best Practice: We strongly recommend using environment variables for sensitive configuration such as API credentials (MDB_MCP_API_CLIENT_ID, MDB_MCP_API_CLIENT_SECRET) and connection strings (MDB_MCP_CONNECTION_STRING) instead of command-line arguments. Environment variables are not visible in process lists and provide better security for your sensitive data.

The MongoDB MCP Server can be configured using multiple methods, with the following precedence (highest to lowest):

1. Command-line arguments
2. Environment variables
3. Configuration File

Configuration Options

View the full README on GitHub