Gemini Collaboration MCP Server
# Gemini Collaboration MCP Server
[English](#) | [한국어](./README.ko.md)
MCP Server for Claude & Gemini Collaboration. Consult Gemini AI for a second opinion or collaborate on code development together.
## Features
### 1. `consult_gemini` - Get a Second Opinion
Ask Gemini for advice, validation, or a different perspective on your work.
**Use cases:**
- Validate your approach
- Get code reviews
- Ask for expert advice on technical problems
- Get a different perspective on implementation choices
### 2. `collaborate_on_code` - Build Together
Collaborate with Gemini to develop code from scratch through iterative dialogue.
**Process:**
1. Create and review PRD together
2. Decide on tech stack together
3. Generate and refine code together
## Installation
### Via npm (Recommended)
```bash
npm install -g gemini-collaboration-mcp
```
### Via GitHub
```bash
git clone https://github.com/henry2craftman/gemini-collaboration-mcp.git
cd gemini-collaboration-mcp
npm install
npm run build
```
## Configuration
### 1. Get Gemini API Key
Get your API key from [Google AI Studio](https://makersuite.google.com/app/apikey)
### 2. Configure Claude Code
Add to your Claude Code MCP settings:
**For npm installation:**
```json
{
"mcpServers": {
"gemini-collaboration": {
"command": "npx",
"args": ["-y", "gemini-collaboration-mcp"],
"env": {
"GEMINI_API_KEY": "your-gemini-api-key-here"
}
}
}
}
```
**For local installation:**
```json
{
"mcpServers": {
"gemini-collaboration": {
"command": "node",
"args": ["path/to/gemini-collaboration-mcp/dist/mcp-server.js"],
"env": {
"GEMINI_API_KEY": "your-gemini-api-key-here"
}
}
}
}
```
### 3. Restart Claude Code
Restart Claude Code to load the MCP server.
## Usage
Once configured, you can use these commands in Claude Code:
### Consult Gemini
```
"Gemini, what do you think about this approach?"
"Ask Gemini to review this code"
"Get Gemini's opinion on this implementation"
```
### Collaborate on Code
```
"Collaborate with Gemini to build a 3D dice game"
"Work with Gemini to create a calculator app"
"Develop a todo list app together with Gemini"
```
## Architecture
This MCP server uses the [AI Orchestration Framework](https://github.com/henry2craftman/ai-orchestration) to:
- Chain AI model interactions
- Manage context between Claude and Gemini
- Execute multi-step collaborative workflows
## Requirements
- Node.js 18 or higher
- Gemini API key
- Claude Code (Anthropic's official CLI)
## Development
```bash
# Install dependencies
npm install
# Build
npm run build
# Run MCP server directly
npm run mcp
# Run interactive chat
npm run chat
```
## License
MIT
## Contributing
Contributions are welcome! Please open an issue or submit a pull request.
## Support
For issues, questions, or suggestions, please open an issue on GitHub.
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: collaborate_on_code is for iterative code development through a structured collaboration process, while consult_gemini is for seeking validation, advice, or a second opinion on decisions or technical problems. There is no overlap in functionality or ambiguity between them.
Both tools follow a consistent verb_noun pattern: collaborate_on_code and consult_gemini. The naming is predictable and readable, with no deviations or mixed conventions, making it easy for agents to understand the action and target.
With only 2 tools, the server feels thin for its purpose of 'Gemini Collaboration,' which suggests a broader scope involving code development and consultation. While the tools are well-defined, the count is too low to provide comprehensive coverage for collaboration workflows, lacking tools for specific actions like reviewing code, managing iterations, or handling feedback loops.
The server has significant gaps in its tool surface for collaboration. It lacks tools for key operations such as reviewing or editing code independently, managing project states, or handling iterative feedback beyond the initial collaboration. This incomplete coverage will likely cause agent failures when trying to perform nuanced or multi-step collaboration tasks.