Gemini MCP Server

Council MCP Server

A Model Context Protocol (MCP) server that enables Claude to collaborate with multiple AI models via OpenRouter. Access 100+ models from Google, Anthropic, OpenAI, Meta, Mistral, and more.

Features

• Multi-Model Support: Access 100+ models via OpenRouter (Gemini, GPT, Claude, Llama, Mistral, etc.)
• Dynamic Model Discovery: List and filter available models by provider, capability, or pricing
• Per-Request Model Override: Use different models for different tasks
• Multiple Collaboration Tools: Code review, brainstorming, test generation, explanations
• Response Caching: Automatic caching for repeated queries

Quick Start

1. Prerequisites

• Python 3.9+
• Claude Desktop or Claude Code
• OpenRouter API Key

2. Installation

# Clone the repository
git clone https://github.com/lbds137/council-mcp-server.git
cd council-mcp-server

# Install dependencies
pip install -r requirements.txt

# Copy and configure environment
cp .env.example .env
# Edit .env and add your OPENROUTER_API_KEY

3. Configuration

Edit .env to configure:

# Your OpenRouter API key (required)
OPENROUTER_API_KEY=sk-or-...

# Model configuration (optional - defaults shown)
COUNCIL_DEFAULT_MODEL=google/gemini-3-pro-preview
COUNCIL_CACHE_TTL=3600
COUNCIL_TIMEOUT=600000

4. Register with Claude

# Install to MCP location
./scripts/install.sh

# Or manually register
claude mcp add council python3 ~/.claude-mcp-servers/council/launcher.py

Available Tools

Core Tools

Model Management

Model Override

All tools support an optional model parameter to use a specific model:

# Use Claude for code review
mcp__council__code_review(
    code="def hello(): print('world')",
    focus="security",
    model="anthropic/claude-3-opus"
)

# Use GPT-4 for brainstorming
mcp__council__brainstorm(
    topic="API design patterns",
    model="openai/gpt-4-turbo"
)

Popular Model Configurations

Google Gemini (Default)

COUNCIL_DEFAULT_MODEL=google/gemini-3-pro-preview

Anthropic Claude

COUNCIL_DEFAULT_MODEL=anthropic/claude-3.5-sonnet

OpenAI GPT-4

COUNCIL_DEFAULT_MODEL=openai/gpt-4-turbo

Meta Llama (Free)

COUNCIL_DEFAULT_MODEL=meta-llama/llama-3.3-70b-instruct:free

Development

Project Structure

council-mcp-server/
├── src/council/           # Main source code
│   ├── main.py           # CouncilMCPServer entry point
│   ├── manager.py        # ModelManager (OpenRouter)
│   ├── providers/        # LLM provider implementations
│   ├── discovery/        # Model discovery and filtering
│   ├── tools/            # MCP tool implementations
│   ├── core/             # Registry and orchestrator
│   └── services/         # Cache and memory
├── tests/                # Test suite
├── scripts/              # Installation scripts
├── server.py             # Bundled single-file server
├── launcher.py           # Launcher with venv support
├── CLAUDE.md            # Claude Code instructions
└── README.md            # This file

Running Tests

# Create virtual environment
python -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run tests
pytest tests/ -v

Building the Bundle

# Generate single-file server.py
python scripts/bundler.py

# Deploy to MCP location
./scripts/install.sh

Updating

To update your local MCP installation after making changes:

./scripts/install.sh

Then restart Claude Desktop/Code.

Troubleshooting

Server not found

# Check registration
claude mcp list

# Re-register if needed
./scripts/install.sh

API Key Issues

# Verify environment variable
echo $OPENROUTER_API_KEY

# Test with list_models tool
mcp__council__list_models(limit=5)

Model Not Available

Use list_models to find available models:

mcp__council__list_models(provider="google")

Version History

• v4.0.0: Council - Multi-model support via OpenRouter
• v3.0.0: Modular architecture with bundler
• v2.0.0: Dual-model support with fallback
• v1.0.0: Initial Gemini integration

License

MIT License - see LICENSE file for details.

Acknowledgments

• Built for Claude using the Model Context Protocol
• Powered by OpenRouter for multi-model access