MCP Server For Local

🚀 MCP Local Server Proxy

A local proxy server and client implementation based on MCP (Multi-Component Platform), offering various AI tool invocation capabilities.

🚀 Quick Start

The MCP Local Server Proxy is a powerful tool that integrates multiple AI functionalities. Here's how you can get started:

Prerequisites

• Python 3.8+
• Node.js (Optional, for running the JavaScript server)
• Chrome browser (for Google Search functionality)
• A camera (for the photo-taking feature)
• At least 4GB of RAM
• A CUDA-compatible GPU (Optional, for accelerating AI computations)

Installation Steps

1. Clone the repository:

git clone https://github.com/yourusername/mcp-server-for-local.git
cd mcp-server-for-local

2. Create and activate a virtual environment:

# Windows
python -m venv .venv
.venv\Scripts\activate

# Linux
python3 -m venv .venv
source .venv/bin/activate

3. Install dependencies:

# Use uv to install dependencies
uv pip install -r requirements.txt

# If you encounter network issues, you can use a domestic mirror
uv pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

4. Configure environment variables:

cp config/.env.example config/.env

Starting the Proxy Server

1. Start the proxy server:

python3 src/mcp/proxy/app.py --port=8080

2. Access http://localhost:8080 in your browser to use the service.

Using the Client

1. Connect to the proxy server:

curl http://localhost:8080/api/weather?city=London

✨ Features

Core Features

• Weather Query: Retrieve real-time weather information for any location worldwide, supporting detailed data such as temperature, humidity, and wind speed.
• Google Search: Intelligently search the internet, supporting multiple languages and advanced search syntax.
• Camera Control: Support photo-taking, video streaming, and micro-expression analysis for emotion recognition.
• Image Generation: Integrate ComfyUI to support text-to-image AI generation.
• Intelligent Conversation: Based on DashScope's AI conversation capabilities, support context understanding and multi-round conversations.

Technical Features

• Cross-platform support (Windows and Linux)
• Modular design for easy extension of new features
• A complete logging system for easy debugging and monitoring
• Support for custom tools and API integration
• High-performance concurrent processing capabilities

📚 Documentation

Project Structure

src/mcp/
├── client/          # Client code
├── proxy/           # Proxy server code
├── tools/           # Tool implementations
├── utils/           # Utility functions
└── config/          # Configuration files

Adding New Features

1. Create a new tool class in the tools directory.
2. Implement the necessary interface methods.
3. Register the new tool in the configuration file.
4. Write test cases.
5. Update the documentation.

🤝 Contribution Guidelines

We welcome issues and pull requests! Before submitting, please ensure that:

1. Your code adheres to the project's coding standards.
2. You have added the necessary tests.
3. You have updated the relevant documentation.
4. All tests pass.

📄 License

This project is licensed under the MIT License.