Gemini MCP Server

An MCP (Model Context Protocol) server that provides access to Google Gemini AI models.

Quick Start

1. Install dependencies:

npm install

2. Create a .env file with your Gemini API key:

GEMINI_API_KEY=your_api_key_here

3. Start the server:

npm run dev

The server will run at http://localhost:3333/mcp

Available Tool

gemini.generateText

Generate text using Google Gemini models.

Parameters:

• prompt (string, required): The text prompt
• model (string, optional): Gemini model to use (default: gemini-2.5-pro)
• temperature (number, optional): Temperature for generation, 0-2 (default: 1)

Returns:

• text: Generated text response
• model: Model used
• temperature: Temperature setting used

Usage Example

import { Client as McpClient } from '@modelcontextprotocol/sdk/client/index.js';
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';

const transport = new StreamableHTTPClientTransport(
  new URL('http://localhost:3333/mcp')
);

const client = new McpClient(
  { name: 'my-client', version: '1.0.0' },
  { capabilities: {} }
);

await client.connect(transport);

const result = await client.callTool({
  name: 'gemini.generateText',
  arguments: {
    prompt: 'Explain AI in simple terms',
    model: 'gemini-2.5-pro',
    temperature: 0.7
  }
});

console.log(result);
await client.close();

Testing

Run the included test client (requires server to be running):

npm test

Configuration

Environment variables:

• GEMINI_API_KEY (required): Your Google Gemini API key
• PORT (optional): Server port (default: 3333)

License

ISC