M

MCP Entry

MongoDB MCP

Allows AI agents to run queries, inspect collections, execute aggregation pipelines, and analyze explain plans against MongoDB clusters. Debug document models and performance issues by having the agent explore data structures directly. Supports MongoDB Atlas federated queries and Atlas Search.

Category Database
Install npm
Runtime Node.js
mongodbdatabasenosql

Use cases

  • Developer inspects document schema to understand data relationships
  • DBA agent analyzes slow query explain plans and suggests index additions
  • Backend engineer prototypes aggregation pipelines before code implementation
  • QA agent verifies test data in collections matches expected values
  • Support agent queries user sessions to diagnose login issues

Key features

  • Claude Desktop
  • Cursor
  • Codex

Frequently Asked Questions

What MongoDB deployments are supported?
Standalone, replica sets, sharded clusters, MongoDB Atlas, and Atlas Data Lake are all supported. Connection strings follow standard MongoDB URI format.
Can agents modify data?
Yes, agents can run insert, update, delete, and aggregation operations with write stages. Use read-only deployments for safety if your use case allows.
How does the agent handle large collections?
Agents should use query filters to limit result sets. For analysis, aggregation pipelines with $limit and $sample are recommended to avoid returning massive datasets.

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