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georgejeffers

Gemini MCP Server

README.md
# gemini-mcp-server

[![smithery badge](https://smithery.ai/badge/@georgejeffers/gemini-mcp-server)](https://smithery.ai/server/@georgejeffers/gemini-mcp-server)

A TypeScript implementation of a Model Context Protocol (MCP) server that integrates with Google's Gemini Pro model.

<a href="https://glama.ai/mcp/servers/ejwvacw7s0">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/ejwvacw7s0/badge" alt="Gemini Server MCP server" />
</a>

## MCP Tools

### generate_text
*From server: gemini*

## Prerequisites

- Node.js 18 or higher
- Google Gemini API key
- TypeScript
- Claude Desktop app

## Installation

### Installing via Smithery

To install Gemini MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@georgejeffers/gemini-mcp-server):

```bash
npx -y @smithery/cli install @georgejeffers/gemini-mcp-server --client claude
```

### Manual Installation
1. Clone the repository:
```bash
git clone https://github.com/GeorgeJeffers/gemini-mcp-server.git
cd gemini-mcp-server
```

2. Install dependencies:
```bash
npm install
```

4. Build:
```bash
npm run build
```

## Claude Desktop Integration

To use this server with Claude Desktop:

1. Open Claude Desktop
2. Go to Settings > Developer
3. Click "Edit Config"
4. Add the following configuration:

```json
{
  "name": "gemini",
  "command": "node",
  "args": ["dist/gemini_mcp_server.js"],
  "env": {
    "GEMINI_API_KEY": "your_api_key_here"
  },
  "cwd": "/path/to/mcp-gemini-server"
}
```

Replace:
- `/path/to/mcp-gemini-server` with the absolute path to where you cloned this repository
- `your_api_key_here` with your actual Google Gemini API key

The server will now be available in Claude Desktop's MCP server list.

## License

MIT

## Author

GeorgeJeffers

TDQS

A3.9/5.0

Scored across 7 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: chat handles conversations, code_execution runs Python, edit_image modifies single images, edit_image_multi handles multiple images, generate_image creates images, generate_text produces text, and generate_with_search adds search grounding. The descriptions clearly differentiate their functions, making misselection unlikely.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., chat, code_execution, edit_image, generate_image, generate_text, generate_with_search). The naming is uniform and predictable across all seven tools, with no deviations in style or convention.

Tool Count5/5

With 7 tools, the count is well-scoped for a Gemini MCP server, covering core AI functionalities like text generation, image handling, code execution, and chat. Each tool earns its place without feeling excessive or insufficient for the server's purpose.

Completeness4/5

The tool surface is nearly complete for a Gemini AI server, covering text generation (with and without search), image generation and editing, code execution, and chat. A minor gap exists in lacking explicit tools for model management or configuration, but core workflows are well-covered and agents can work around this.

Maintenance

ActivityInactive
ResponsivenessNo issues