MCP MongoDB Integration

Name: MCP MongoDB Integration
Author: the-sukhsingh

@the-sukhsingh

关于 MCP MongoDB Integration

This project demonstrates the integration of MongoDB with the Model Context Protocol (MCP) to provide AI assistants with database interaction capabilities.

#mongodb #mongoose #mcp #mongodb-database #genai-chatbot #google-gemini-ai #mcp-server #mcp-client

基本信息

分类

数据库

运行时

node

传输方式

stdio

发布者

the-sukhsingh

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcpmongo": {
      "command": "node",
      "args": [
        "index.js"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP MongoDB Integration?

MCP MongoDB Integration connects MongoDB with the Model Context Protocol (MCP) to give AI assistants direct database interaction capabilities. It consists of an MCP server that exposes MongoDB operations as tools and a client-side terminal chatbot that uses Google’s Gemini AI to invoke those tools.

How to use MCP MongoDB Integration?

Set up the server by navigating to mcp-mongo-project, install dependencies, create a .env file with MONGODB_URI and MONGODB_NAME, then start with npm start. Set up the client by navigating to client-side, install dependencies, create a .env with GEMINI_API_KEY, and run node index.js. The client connects to the server via Server-Sent Events (SSE) and lets you chat with Gemini to perform MongoDB operations.

Key features of MCP MongoDB Integration?

Full CRUD operations exposed as MCP tools
Gemini AI integration for natural language queries
Terminal-based chatbot interface
Supports find, insert, update, delete, and aggregation
Count documents, list and create collections
Communicates via Server-Sent Events (SSE)

Use cases of MCP MongoDB Integration

Query collections and documents using natural language
Insert, update, or delete documents through a chat interface
Run aggregation pipelines via AI-driven tool calls
List or create new collections interactively

FAQ from MCP MongoDB Integration

What MongoDB tools are available?

The server exposes 12 tools: findDocuments, findOneDocument, insertOneDocument, insertManyDocuments, updateOneDocument, updateManyDocuments, deleteOneDocument, deleteManyDocuments, aggregateDocuments, countDocuments, listCollections, and createCollection.

What are the prerequisites?

You need Node.js v14 or higher, a MongoDB instance (local or remote), and a Google Gemini API key.

How does the integration work?

The MCP server connects to MongoDB and exposes operations as tools. The client sends user queries to Gemini AI, which decides when to call a tool. The tool call is forwarded to the MCP server, executed, and the result is included in Gemini’s response.

What environment variables are required?

For the server: MONGODB_URI (connection string) and MONGODB_NAME (database name). For the client: GEMINI_API_KEY (Google Gemini API key).

What license does this project use?

It is licensed under ISC.

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