MongoDB MCP 服务器

PyMongo

Provides a comprehensive set of tools for interacting with MongoDB databases from Python applications.

MongoDB

Connects to MongoDB databases and MongoDB Atlas clusters via the Model Context Protocol.

Mongo

Enables Large Language Models (LLMs) to interact with MongoDB databases for schema inspection and operation execution.

MongoDB Lens

Provides a local Model Context Protocol (MCP) server for interacting with MongoDB databases using natural language queries.

Mongo

Enables Large Language Models (LLMs) to directly interact with MongoDB databases using natural language.

Go-Zero Assistant

Scaffold and generate go-zero projects, including APIs, RPC services, and database models, with AI assistance.

MongoDB

Enables Large Language Models (LLMs) to inspect MongoDB schemas and execute aggregation pipelines.

Mongo

Enables LLMs to interact with MongoDB databases through natural language.

Memory Bank

Provides a powerful, vector-native memory bank for AI agents, offering persistent, searchable, and shareable memory with multiple database backends.

Vector

Manages standardized collection operations across multiple vector database technologies for AI agents.

MongoDB Atlas

Manages MongoDB Atlas projects, clusters, users, and network access through the Model Context Protocol (MCP).

Db

Manages access and operations across multiple database types, offering robust OAuth 2.0 authentication, granular tool filtering, and fine-grained access control.

MongoDB

Enables AI assistants to directly query and analyze MongoDB databases through standardized Model Context Protocol (MCP) tools and resources.

MongoDB and MySQL Server

Enables AI models to interact with MySQL and MongoDB databases through a standardized interface.

Florentine

Enables natural language querying for MongoDB data, transforming questions into aggregations for AI agents and desktop applications.

MongTap

Serves MongoDB-compatible database functionality by generating data statistically using DataFlood ML models, enabling natural language interactions for large language models.

RAG Agent

Builds reliable, context-aware AI agents by integrating LangGraph with Model Context Protocol for semantic search, grounded responses, and automated evaluation.

Mongo

Connects Large Language Models to MongoDB databases for CRUD operations using natural language.

Legacy MongoDB

Enables AI models to safely access and analyze data from legacy MongoDB instances (versions 2.6-3.6) using a Model Context Protocol (MCP) interface.

Mongo

Queries MongoDB databases using the Model Context Protocol.