# MongoDB MCP

```json
{
  "name": "MongoDB MCP",
  "slug": "mongodb_mcp",
  "url": "https://composio.dev/toolkits/mongodb_mcp",
  "markdown_url": "https://composio.dev/toolkits/mongodb_mcp.md",
  "logo_url": "https://logos.composio.dev/api/mongodb_mcp",
  "categories": [
    "developer tools & devops"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-09-30T05:32:41.129Z"
}
```

![MongoDB MCP logo](https://logos.composio.dev/api/mongodb_mcp)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with MongoDB MCP or direct API to explore clusters, query collections, manage indexes, and inspect performance metrics through natural language.

## Summary

MongoDB MCP is MongoDB's managed interface for accessing Atlas resources and data.
Use it for secure, centralized access to clusters, databases, and collections.

## Categories

- developer tools & devops

## Toolkit Details

- Tools: 41

## Images

- Logo: https://logos.composio.dev/api/mongodb_mcp

## Authentication

- **S2s Oauth2**
  - Type: `custom`
  - Description: S2s Oauth2 authentication for MongoDB MCP.
  - Setup:
    - Configure S2s Oauth2 credentials for MongoDB MCP.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- List collections in my production database
- Query top slow queries from cluster
- Create index on users.email field

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MONGODB_MCP_AGGREGATE` | Aggregate | Run an aggregation against a MongoDB collection |
| `MONGODB_MCP_AGGREGATE_DB` | Aggregate-db | Run an aggregation against a MongoDB database |
| `MONGODB_MCP_ATLAS_CREATE_ACCESS_LIST` | Atlas-create-access-list | Allow Ip/CIDR ranges to access your MongoDB Atlas clusters. |
| `MONGODB_MCP_ATLAS_CREATE_CLUSTER` | Atlas-create-cluster | Create a MongoDB Atlas cluster (M10–M80, replica set or single shard, single or multi-region). 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. For encryption at rest, the CMK provider must already have a valid configuration in the Atlas 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. Note to LLM: Omit instance size unless specified by the user. If provider and regions are not already known, ask for both together in a single question before calling this tool. Common, non-exhaustive region default mappings by provider: AWS: "East Coast"/"Virginia"/"US East" → US_EAST_1, "Ohio" → US_EAST_2, "California"/"West Coast" → US_WEST_2, "Southeast Asia"/"APAC"/"Singapore" → AP_SOUTHEAST_1, "Europe"/"EU"/"Ireland" → EU_WEST_1. GCP: "Central US" → CENTRAL_US, "Western US" → WESTERN_US, "Southeast Asia"/"APAC" → SOUTHEASTERN_ASIA_PACIFIC, "Europe"/"EU" → WESTERN_EUROPE. AZURE: "East US" → US_EAST_2, "West US" → US_WEST_2, "Europe North" → EUROPE_NORTH, "Europe West" → EUROPE_WEST. Default recommendation: AWS US_EAST_1. User-specified regions not present in the mapping MUST be respected, rely on the tool to surface errors if a region is not supported. |
| `MONGODB_MCP_ATLAS_CREATE_DB_USER` | Atlas-create-db-user | Create an MongoDB Atlas database user |
| `MONGODB_MCP_ATLAS_CREATE_FREE_CLUSTER` | Atlas-create-free-cluster | Create a free MongoDB Atlas cluster |
| `MONGODB_MCP_ATLAS_CREATE_PROJECT` | Atlas-create-project | Create a MongoDB Atlas project |
| `MONGODB_MCP_ATLAS_GET_PERFORMANCE_ADVISOR` | 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 |
| `MONGODB_MCP_ATLAS_INSPECT_ACCESS_LIST` | Atlas-inspect-access-list | Inspect Ip/CIDR ranges with access to your MongoDB Atlas clusters. |
| `MONGODB_MCP_ATLAS_INSPECT_CLUSTER` | Atlas-inspect-cluster | Inspect metadata of a MongoDB Atlas cluster |
| `MONGODB_MCP_ATLAS_LIST_ALERTS` | 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. |
| `MONGODB_MCP_ATLAS_LIST_CLUSTERS` | Atlas-list-clusters | List MongoDB Atlas clusters |
| `MONGODB_MCP_ATLAS_LIST_DB_USERS` | Atlas-list-db-users | List MongoDB Atlas database users |
| `MONGODB_MCP_ATLAS_LIST_ORGS` | Atlas-list-orgs | List MongoDB Atlas organizations |
| `MONGODB_MCP_ATLAS_LIST_PROJECTS` | Atlas-list-projects | List MongoDB Atlas projects. |
| `MONGODB_MCP_ATLAS_LOAD_SAMPLE_DATASET` | 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. |
| `MONGODB_MCP_ATLAS_PAUSE_RESUME_CLUSTER` | Atlas-pause-resume-cluster | Pause or resume a dedicated (M10+) MongoDB Atlas cluster (Free and Flex clusters cannot be paused). Pause: paused clusters are unavailable for connections and do not incur compute costs. If the cluster being paused is the current active connection, it will be automatically disconnected. Returns an error if the cluster is already paused or not in a pausable state (must be IDLE). Resume: the cluster will not be immediately available after resuming. Use the atlas-inspect-cluster tool to poll the cluster state for readiness (state: IDLE). If the cluster is not paused, resuming it is a no-op. |
| `MONGODB_MCP_ATLAS_STREAMS_BUILD` | 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. |
| `MONGODB_MCP_ATLAS_STREAMS_DISCOVER` | 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. |
| `MONGODB_MCP_ATLAS_STREAMS_MANAGE` | 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. |
| `MONGODB_MCP_ATLAS_STREAMS_TEARDOWN` | 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. |
| `MONGODB_MCP_ATLAS_UPGRADE_CLUSTER` | Atlas-upgrade-cluster | Upgrade a MongoDB Atlas cluster tier. Upgrades Free (M0) clusters to Flex or M10 Dedicated, or Flex clusters to M10 Dedicated. The upgrade path is determined automatically from the current tier unless overridden with targetTier. Note to LLM: If provider and region are not already known, ask for both together in a single question before calling this tool. Common region mappings by provider (default recommendation: AWS US_EAST_1): AWS: "East Coast"/"Virginia"/"US East" → US_EAST_1, "Ohio" → US_EAST_2, "California"/"West Coast" → US_WEST_2, "Southeast Asia"/"APAC"/"Singapore" → AP_SOUTHEAST_1, "Europe"/"EU"/"Ireland" → EU_WEST_1. GCP: "Central US" → CENTRAL_US, "Western US" → WESTERN_US, "Southeast Asia"/"APAC" → SOUTHEASTERN_ASIA_PACIFIC, "Europe"/"EU" → WESTERN_EUROPE. AZURE: "East US" → US_EAST_2, "West US" → US_WEST_2, "Europe"/"EU" → EUROPE_NORTH. |
| `MONGODB_MCP_COLLECTION_INDEXES` | Collection-indexes | Describe the indexes for a collection |
| `MONGODB_MCP_COLLECTION_SCHEMA` | Collection-schema | Describe the schema for a collection |
| `MONGODB_MCP_COLLECTION_STORAGE_SIZE` | Collection-storage-size | Gets the size of the collection |
| `MONGODB_MCP_COUNT` | Count | Gets the number of documents in a MongoDB collection using db.collection.count() and query as an optional filter parameter |
| `MONGODB_MCP_CREATE_COLLECTION` | Create-collection | Creates a new collection in a database. If the database doesn't exist, it will be created automatically. |
| `MONGODB_MCP_CREATE_INDEX` | Create-index | Create an index for a collection |
| `MONGODB_MCP_DB_STATS` | Db-stats | Returns statistics that reflect the use state of a single database |
| `MONGODB_MCP_DELETE_MANY` | Delete-many | Removes all documents that match the filter from a MongoDB collection |
| `MONGODB_MCP_DROP_COLLECTION` | Drop-collection | Removes a collection or view from the database. The method also removes any indexes associated with the dropped collection. |
| `MONGODB_MCP_DROP_DATABASE` | Drop-database | Removes the specified database, deleting the associated data files |
| `MONGODB_MCP_DROP_INDEX` | Drop-index | Drop an index for the provided database and collection. |
| `MONGODB_MCP_EXPLAIN` | Explain | Returns statistics describing the execution of the winning plan chosen by the query optimizer for the evaluated method |
| `MONGODB_MCP_FIND` | Find | Run a find query against a MongoDB collection |
| `MONGODB_MCP_INSERT_MANY` | 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. |
| `MONGODB_MCP_LIST_COLLECTIONS` | List-collections | List all collections for a given database |
| `MONGODB_MCP_LIST_DATABASES` | List-databases | List all databases for a MongoDB connection |
| `MONGODB_MCP_REMOTE_ATLAS_CONNECT` | Remote-atlas-connect | Connect to MongoDB Atlas cluster |
| `MONGODB_MCP_RENAME_COLLECTION` | Rename-collection | Renames a collection in a MongoDB database |
| `MONGODB_MCP_UPDATE_MANY` | 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. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute MongoDB MCP Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute MongoDB MCP actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'YOUR_SPECIFIC_PROMPT_HERE'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for MongoDB MCP
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

```typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to MongoDB MCP tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('YOUR_SPECIFIC_PROMPT_HERE')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native MongoDB MCP Integration

- Supports both MongoDB MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable tool execution
- Rich coverage for reading, writing, and querying your MongoDB MCP data

### 2. Managed Auth

- Built-in OAuth handling with automatic token refresh and rotation
- Central place to manage, scope, and revoke MongoDB MCP access
- Per user and per environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access MongoDB MCP
- Scoped, least privilege access to MongoDB MCP resources
- Full audit trail of agent actions to support review and compliance

## Use MongoDB MCP with any AI Agent Framework

Choose a framework you want to connect MongoDB MCP with:

- [ChatGPT](https://composio.dev/toolkits/mongodb_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/mongodb_mcp/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/mongodb_mcp/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/mongodb_mcp/framework/atomic-agent)

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## Frequently Asked Questions

### Do I need my own developer credentials to use MongoDB MCP with Composio?

Yes, MongoDB MCP requires you to configure your own S2S OAuth2 credentials. Once set up, Composio handles token storage, refresh, and lifecycle management for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)