Content
# Gemini MCP Server
A Model Context Protocol (MCP) server that provides Google Gemini AI
capabilities as tools. Built with Deno and TypeScript.
## Features
- **ask_gemini**: Unified AI assistant powered by Gemini 3 Pro with built-in
Google Search and URL analysis capabilities
## Prerequisites
- [Deno](https://deno.land/) (v1.40+)
- Google Gemini API key ([Get one here](https://ai.google.dev/))
## Installation
### Option 1: Use JSR Package (Recommended)
The easiest way is to use the published JSR package directly in your Claude
Desktop configuration:
```bash
# No installation needed! Use jsr:@cong/gemini-mcp directly in your Claude config
```
### Option 2: From Source
1. Clone this repository:
```bash
git clone <repository-url>
cd gemini-mcp
```
2. Set your environment variables:
```bash
export GEMINI_API_KEY=your_api_key_here
export GEMINI_MODEL=gemini-3-pro-preview
```
## Usage
### Start the Server
```bash
# Set your environment variables first
export GEMINI_API_KEY=your_api_key_here
export GEMINI_MODEL=gemini-3-pro-preview
# Development mode (with watch)
deno task dev
# Production mode
deno task start
```
### Testing with MCP Inspector
To test the server with the MCP Inspector, make sure your environment variables
are set:
```bash
# Set environment variables in your shell
export GEMINI_API_KEY=your_api_key_here
export GEMINI_MODEL=gemini-3-pro-preview
# Install MCP Inspector if you haven't already
npm install -g @modelcontextprotocol/inspector
# Run the inspector
npx @modelcontextprotocol/inspector src/server.ts
```
**Important**: The environment variables must be set in the same shell where you
run the MCP Inspector.
### Run Tests
```bash
# Run all tests
deno task test
# Run tests with watch mode
deno task test:watch
```
### Code Quality
```bash
# Format code
deno fmt
# Lint code
deno lint
```
## MCP Tool
### ask_gemini
The unified AI assistant powered by Gemini 3 Pro with built-in Google Search and
URL analysis capabilities.
**Parameters:**
- `prompt` (required): Your question or request. Include URLs directly in the
text for analysis.
**Example:**
```json
{
"name": "ask_gemini",
"arguments": {
"prompt": "What are the latest developments in quantum computing? Please analyze this paper: https://arxiv.org/abs/2301.01234"
}
}
```
**Capabilities:**
- 🔍 Automatically searches the web for current information
- 📄 Analyzes URLs mentioned in your prompt text
- 🧠 Uses Gemini 3 Pro with thinking capabilities, urlContext and googleSearch
tools
- 📚 Provides comprehensive, well-sourced answers with enhanced reasoning
## Dependencies
- [@modelcontextprotocol/sdk](https://github.com/modelcontextprotocol/typescript-sdk) -
MCP TypeScript SDK
- [@google/generative-ai](https://github.com/google/generative-ai-js) - Google
Gemini API client
- [zod](https://github.com/colinhacks/zod) - Runtime type validation
- [@std/assert](https://jsr.io/@std/assert) - Deno standard library assertions
## Development
This project uses Deno with TypeScript. Key development commands:
- `deno task dev` - Start development server with watch mode
- `deno task test` - Run test suite
- `deno cache src/server.ts` - Cache dependencies
- `deno fmt` - Format code
- `deno lint` - Lint code
## Troubleshooting
### Environment Variable Issues
If you get environment variable errors:
1. **Verify your environment variables are set**:
```bash
echo $GEMINI_API_KEY
echo $GEMINI_MODEL
```
2. **For MCP Inspector testing**, ensure both variables are set in the same
terminal:
```bash
export GEMINI_API_KEY=your_api_key_here
export GEMINI_MODEL=gemini-3-pro-preview
npx @modelcontextprotocol/inspector src/server.ts
```
3. **Check the server logs**: When the server starts, it will show
`(API Key: configured)` to confirm your key is loaded.
## Support
- [Google Gemini API Documentation](https://ai.google.dev/gemini-api/docs)
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [Deno Documentation](https://docs.deno.com/)
## Claude Desktop Configuration
To use this MCP server with Claude Desktop, add it to your Claude configuration:
### macOS/Linux/Windows
Edit your Claude configuration file:
- **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
```json
{
"mcpServers": {
"gemini": {
"command": "deno",
"args": [
"run",
"--allow-net",
"--allow-env",
"jsr:@cong/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your_api_key_here",
"GEMINI_MODEL": "gemini-3-pro-preview"
}
}
}
}
```
### Local Development
If you're running from source code:
```json
{
"mcpServers": {
"gemini": {
"command": "deno",
"args": [
"run",
"--allow-net",
"--allow-env",
"src/server.ts"
],
"env": {
"GEMINI_API_KEY": "your_api_key_here",
"GEMINI_MODEL": "gemini-3-pro-preview"
}
}
}
}
```
## Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: `deno task test`
5. Format code: `deno fmt`
6. Submit a pull request
## License
MIT License - see [LICENSE](LICENSE) file for details.
