"MongoDB" matching MCP servers:

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.

Enables interaction with MongoDB databases through the Model Context Protocol, supporting CRUD operations, secure connections, and easy IDE integration.

Provides read-only access to legacy MongoDB instances (<4.0) via the Model Context Protocol, enabling AI models to query databases, collections, and run aggregations safely.

Enables interaction with MongoDB databases through complete CRUD operations including connecting, creating, reading, updating, and deleting documents with support for filtering, pagination, and automatic ObjectId serialization.

Provides a standardized interface for AI assistants to interact with MongoDB databases, enabling CRUD operations, schema analysis, and database management through the Model Context Protocol.

A powerful Model Context Protocol (MCP) server implementation that provides standardized interaction with MongoDB databases, supporting complete CRUD operations, async patterns, and real-time updates via SSE.

Enables querying and analyzing the MongoDB sample_mflix movie dataset through natural language, supporting searches by title, genre, actors, directors, ratings, and providing aggregate statistics like counts and averages.

An autonomous MCP server that enables LLMs to intelligently query and analyze MongoDB databases by reverse-engineering schemas, proving relationships, and enforcing security safeguards like PII masking and query limits.

Enables basic banking operations (CRUD) with persistent MongoDB storage, supporting account management and money transfers.

Enables basic banking operations such as account creation, deposits, withdrawals, and transfers using MongoDB for persistent storage.

A MongoDB multi-instance query service built on MCP that provides intelligent database structure discovery, semantic analysis, and natural language query generation for MongoDB databases.

MCP server for Hydra ETL: lets AI assistants write declarative YAML ETL pipelines (CSV, Parquet, PostgreSQL, MySQL, MongoDB, APIs) and validate them before any data is read or written.

A multi-database MCP server supporting MySQL, PostgreSQL, MongoDB, and SQLite with read-only and read-write query capabilities, schema inspection, and SSH tunneling, all without Docker.

A Middleware/Control Plane server that allows AI code agents to securely execute queries against various databases (PostgreSQL, MySQL, MongoDB, Oracle) without directly exposing credentials.

A production-grade MCP server for secure MongoDB CRUD operations with filtering, pagination, health monitoring, and rate limiting.

Enables MCP clients to inspect and operate SQLite, PostgreSQL, MySQL/MariaDB, Oracle, SQL Server and MongoDB through 16 tools covering schema discovery, parameterized SQL reads and transactions, MongoDB document operations, and concurrent hybrid SQL/MongoDB queries. Runs locally over stdio or loopback HTTP with pooled connections, bounded concurrency, row and response limits, and read-only defaults.

Enables management of culinary recipes through web scraping from sites like Marmiton.org, recipe generation, ingredient management, and querying a MongoDB database of recipes, comments, users, and utensils.

Enables AI agents to securely query PostgreSQL with pgvector, DynamoDB, and MongoDB Atlas with Vector Search through a read-only, allowlisted MCP interface.

Provides access to Allen Institute for Neural Dynamics (AIND) metadata and data assets through MongoDB queries, aggregation pipelines, NWB file exploration, and AI-powered data summaries.

Equips AI agents with tools to validate Pydantic document models, search architectural patterns, deploy project scaffolding, retrieve blueprints and manuals, and generate repository CRUD classes for a synchronous/asynchronous MongoDB engine.