MCP Host Server with LLM Integration

A comprehensive Model Context Protocol (MCP) host server that integrates multiple MCP servers with your LLM configuration, featuring Playwright MCP for browser automation and a custom MCP server for LLM-powered tasks.

🚀 Features

• Custom MCP Host Server: Unified interface for multiple MCP servers

• LLM Integration: Uses your existing OpenAI GPT-4o configuration

• Playwright MCP Integration: Browser automation capabilities

• Interactive User Interface: Command-line interface for easy interaction

• Multiple Transport Support: HTTP, SSE, and STDIO transports

• Task Orchestration: Complex task execution using available tools and LLM reasoning

Related MCP server: Browser Use Heroku

📋 Prerequisites

• Python 3.10 or higher

• Node.js and npm (for Playwright MCP)

• OpenAI API key

🛠️ Installation

1. Clone/Download the Project

# If you have the files, navigate to the directory
cd mcp

2. Run Setup Script

python setup.py

This will:

• Install Python dependencies

• Install Playwright MCP server

• Install Playwright browsers

• Create necessary directories

• Set up configuration files

3. Configure Environment

# Copy the example environment file
cp .env.example .env

# Edit .env and add your OpenAI API key
# OPENAI_API_KEY=your_actual_api_key_here

4. Test Installation

python test_setup.py

🎯 Usage

Interactive Mode

Start the interactive interface:

python user_interface.py --interactive

Available Commands

General Commands

• help - Show available commands

• status - Show system status

• history - Show command history

• quit - Exit the application

Playwright Commands

• navigate <url> - Navigate to a webpage

• screenshot [filename] - Take a screenshot

• click <selector> - Click an element

• fill <selector> <text> - Fill a form field

• content - Get page content

• wait <selector> - Wait for element

• js <script> - Execute JavaScript

• pdf [filename] - Save page as PDF

LLM Commands

• process <text> [task] - Process text with LLM

• generate <topic> [type] [length] - Generate content

• answer <question> [context] - Answer a question

• brainstorm <topic> [num] [category] - Generate ideas

• format <data> <from> <to> - Format data between formats

Complex Commands

• task <description> - Execute complex task using available tools

• list-tools [client] - List available tools

Command Line Mode

Execute single commands:

# Check status
python user_interface.py --command status

# Navigate to a page
python user_interface.py --command navigate --args https://example.com

# Take a screenshot
python user_interface.py --command screenshot --args webpage.png

📁 Project Structure

mcp/
├── llm_config.py              # Your LLM configuration
├── mcp_client.py              # MCP client implementation
├── custom_mcp_server.py       # Custom MCP server with LLM tools
├── playwright_mcp_config.py   # Playwright MCP configuration
├── user_interface.py          # Interactive user interface
├── setup.py                   # Setup script
├── test_setup.py              # Test script
├── requirements.txt           # Python dependencies
├── .env.example               # Environment variables example
└── README.md                  # This file

🔧 Configuration

MCP Server Configuration

The system uses the following MCP servers:

1. Playwright MCP: Browser automation

   {
     "command": "npx",
     "args": ["@playwright/mcp@latest", "--headless", "--isolated"]
   }

2. Custom LLM MCP: Text processing and generation

   {
     "command": "python",
     "args": ["custom_mcp_server.py"]
   }

Environment Variables

# Required
OPENAI_API_KEY=your_openai_api_key

# Optional
LOG_LEVEL=INFO
NODE_ENV=production
PLAYWRIGHT_BROWSERS_PATH=0

🧪 Examples

Browser Automation Example

mcp> navigate https://httpbin.org/html
mcp> screenshot test.png
mcp> content
mcp> pdf webpage.pdf

LLM Processing Example

mcp> process "Climate change is a major global challenge" analyze
mcp> generate "renewable energy solutions" article medium
mcp> answer "What is photosynthesis?" "Plants convert sunlight to energy"
mcp> brainstorm "mobile app ideas" 5 business

Complex Task Example

mcp> task "Navigate to a news website, take a screenshot, extract the main headlines, and summarize them"

🐛 Troubleshooting

Common Issues

1. Playwright browsers not installed

   npx playwright install

2. Python dependencies missing

   pip install -r requirements.txt

3. OpenAI API key not set

   • Check your .env file

   • Ensure the key starts with sk-

4. Node.js/npm not found

   • Install Node.js from https://nodejs.org/

Debug Mode

Run with detailed logging:

LOG_LEVEL=DEBUG python user_interface.py --interactive

Testing Individual Components

# Test LLM configuration
python -c "from llm_config import llm; print('LLM OK')"

# Test MCP client
python -c "from mcp_client import MCPClient; print('MCP Client OK')"

# Test Playwright MCP
npx @playwright/mcp@latest --help

🔄 Integration with Other Systems

Claude Desktop Integration

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "custom-mcp-host": {
      "command": "python",
      "args": ["path/to/mcp/user_interface.py", "--interactive"]
    }
  }
}

Cursor Integration

Add to your mcp.json:

{
  "mcpServers": {
    "custom-mcp-host": {
      "command": "python",
      "args": ["path/to/mcp/user_interface.py"]
    }
  }
}

📚 API Reference

MCPClient Class

from mcp_client import MCPClient

client = MCPClient(config)
await client.connect()
tools = await client.list_tools()
result = await client.call_tool("tool_name", parameters)

PlaywrightMCPController Class

from playwright_mcp_config import PlaywrightMCPController

controller = PlaywrightMCPController()
await controller.initialize()
await controller.navigate_to_page("https://example.com")

MCPHostServer Class

from mcp_client import MCPHostServer

host = MCPHostServer()
host.add_client("name", config)
await host.start_clients()
result = await host.execute_command("client", "command", params)

🤝 Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Test with python test_setup.py

5. Submit a pull request

📄 License

This project is licensed under the MIT License.

🆘 Support

For issues and questions:

1. Check the troubleshooting section

2. Run the test suite: python test_setup.py

3. Check logs in the logs/ directory

4. Refer to the FastMCP documentation: https://gofastmcp.com/

🎉 Acknowledgments

• FastMCP - Python framework for MCP

• Playwright MCP - Browser automation

• OpenAI - LLM capabilities

• Model Context Protocol - Standard protocol