AI Collaboration MCP Server
A streamlined Model Context Protocol (MCP) server that provides enhanced AI collaboration tools for VS Code with automatic project context injection and conversation history.
🚀 Features
- Multi-Provider Support: Claude, GPT-4, Gemini, and Ollama
- Workspace-Specific Conversation History: Each project gets isolated conversation memory
- Automatic Context Injection: Project files, structure, and README automatically included
- Dynamic Workspace Management: Switch between projects seamlessly
- API Call Management: Rate limiting (3 calls per provider per hour)
- Streamlined Tools: Just 4 essential tools that work together
🛠️ Tools Available
1. #set_workspace
Set the current workspace directory for project-specific conversation history and context.
Usage in VS Code:
@workspace use #set_workspace with workspace_path="/path/to/your/project"
2. #consult_ai
Get expert advice from a specific AI provider with full project context.
Usage in VS Code:
@workspace use #consult_ai with claude about error handling best practices
3. #multi_ai_research
Get perspectives from multiple AI providers on complex questions.
Usage in VS Code:
@workspace use #multi_ai_research to analyze authentication approaches
4. #mandatory_execute
Force tool execution with explicit commands.
Usage in VS Code:
@workspace !consult_ai
@workspace use #multi_ai_research
📦 Installation
Prerequisites
- Node.js 18+
- VS Code with MCP support
- API keys for desired AI providers
1. Clone and Setup
git clone https://github.com/yourusername/ai-collaboration-mcp-server.git
cd ai-collaboration-mcp-server
npm install
2. Configure Environment Variables
Create a .env file:
# AI Provider API Keys (add the ones you want to use)
ANTHROPIC_API_KEY=your_claude_key_here
OPENAI_API_KEY=your_openai_key_here
GEMINI_API_KEY=your_gemini_key_here
# Ollama Configuration (for local AI)
OLLAMA_BASE_URL=http://localhost:11434
OLLAMA_MODEL=llama3.2:latest
3. Build the Server
npm run build
4. Configure VS Code MCP
Option A: Workspace-specific (recommended for testing)
Create .vscode/mcp.json in your project:
{
"servers": {
"ai-collaboration": {
"type": "stdio",
"command": "node",
"args": ["/path/to/ai-collaboration-mcp-server/build/index.js"],
"env": {
"ANTHROPIC_API_KEY": "your_key_here",
"OPENAI_API_KEY": "your_key_here",
"GEMINI_API_KEY": "your_key_here",
"OLLAMA_BASE_URL": "http://localhost:11434"
}
}
}
}
Option B: Global configuration (for all projects)
Create ~/.vscode/mcp.json:
{
"servers": {
"ai-collaboration": {
"type": "stdio",
"command": "node",
"args": ["/absolute/path/to/ai-collaboration-mcp-server/build/index.js"],
"env": {
"ANTHROPIC_API_KEY": "your_key_here",
"OPENAI_API_KEY": "your_key_here",
"GEMINI_API_KEY": "your_key_here",
"OLLAMA_BASE_URL": "http://localhost:11434"
}
}
}
}
5. Enable MCP Auto-start (Optional)
Add to your VS Code settings.json:
{
"chat.mcp.autostart": "newAndOutdated"
}
🎯 Usage
First Time Setup Per Project:
- Restart VS Code after configuration
- Open VS Code chat (sidebar or
Cmd+Shift+I) - Set workspace for your project:
@workspace use #set_workspace with workspace_path="/full/path/to/your/project"
Daily Usage:
- Use the AI tools:
@workspace use #consult_ai with claude about my code@workspace use #multi_ai_research to compare approaches@workspace !consult_ai(force execution)
When Switching Projects:
- Set new workspace:
@workspace use #set_workspace with workspace_path="/path/to/other/project"
💡 Tip: Each project gets its own .mcp-conversation-history.json file for isolated conversation memory.
⚠️ Important Syntax Note
When using @workspace in VS Code, MCP tool names must be prefixed with #:
✅ Correct: @workspace use #consult_ai with claude about my code
❌ Wrong: @workspace use consult_ai with claude about my code
Without @workspace, no # is needed:
✅ Also correct: use consult_ai with claude about my code
🔧 Development
Run in Development Mode
npm run dev
Test the Server
npm test
Debug with MCP Inspector
npx @modelcontextprotocol/inspector node build/index.js
🧠 How It Works
Enhanced Context Injection
Every tool call automatically includes:
- Project structure and files
- README and package.json content
- Relevant conversation history
- Current workspace context
Conversation History
- Persistent file-based history (
.mcp-conversation-history.json) - Smart relevance filtering
- Cross-session context continuity
API Management
- Rate limiting per provider (3 calls/hour)
- Automatic retry with exponential backoff
- Clear error handling and user feedback
🔒 Security Notes
- API keys are stored in MCP configuration (keep them secure)
- Conversation history is stored locally
- No data sent to external services except AI provider APIs
🤝 Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Test thoroughly
- Submit a pull request
📄 License
MIT License - see LICENSE file for details
🆘 Troubleshooting
MCP Server Won't Start
- Check
Cmd+Shift+P→ "MCP: List Servers" - Verify file paths in configuration
- Check VS Code Output panel for errors
- Ensure Node.js and dependencies are installed
API Keys Not Working
- Verify keys are correctly set in MCP configuration
- Check for typos or extra spaces
- Ensure keys have proper permissions
Tools Not Appearing
- Restart VS Code completely
- Try
@workspacein chat to trigger MCP loading - Check MCP server logs for errors
🌟 Why This Approach?
This streamlined server demonstrates that smart consolidation beats feature proliferation:
- 3 core tools instead of 7+ specialized ones
- Enhanced context shared across all tools
- Easier maintenance and debugging
- Better user experience with consistent functionality
- Reduced cognitive load - focus on what you want, not which tool to use
Perfect for teams wanting powerful AI collaboration without complexity!