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 @workspace in 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!

AI Collaboration MCP Server