MCP Connect

🚀 MCPOmni Connect

MCPOmni Connect is a powerful intelligent client tool designed for modern AI applications. It supports multi - language interaction and various model interfaces. By integrating multiple functional modules, it enables unified management and operation of multiple MCP servers.

🚀 Quick Start

📦 Installation

Local Installation

# Clone the repository
$ git clone https://github.com/Abiorh001/mcp_omni_connect.git
# Navigate to the project directory
$ cd mcp_omni_connect
# Install dependencies
$ pip install -r requirements.txt

Server Deployment

# Start the MCP server
$ python server.py
# Access the console
# Default address: http://localhost:8000

✨ Features

Core Features

• Multi - language Support: Natively supports interaction in multiple languages such as English and Chinese.
• Model Compatibility: Fully supports mainstream AI models like OpenAI, OpenRouter, and Groq.
• Toolchain Integration: Built - in useful tools like Google Maps API and EV network API.
• Resource Management: Provides advanced functions such as document analysis and data processing.
• Intelligent Conversation: Has functions like automatic tool chaining and context understanding.

Detailed Features

Multi - language Interaction

Users can choose to communicate in English or Chinese as needed, and the system will automatically recognize and respond.

# Example: Interact with AI in Chinese
$ mcp_client_new1
> 分析 /path/to/document.pdf 的内容

Model Support

• OpenAI Models: Fully compatible with all models provided by OpenAI.
• Native Function Calling: Supports models with function - calling capabilities.
• ReAct Agent Fallback: Provides adaptation support for legacy models.

Toolchain Integration

The system has multiple built - in useful tools and supports the following operations:

# Example: Automatic charging station query process
1. Use Google Maps API to get the geographical location of Silicon Valley
2. Search for surrounding charging piles
3. Call the EV network API to query the station status
4. Integrate the results and output a report

💻 Usage Examples

Basic Usage

Connect to the MCP Server

# Example: Connect to the server with default configuration
$ mcp_client_new1
> /start

View Help Information

# Example: Get a list of available commands
$ help
# Or
$ ?

Advanced Usage

Cross - server Execution

# Example: Execute an analysis task across multiple servers
User: "Analyze the sales data in /path/to/sales.csv and generate a report"

# The system automatically executes:
1. Load the data file locally
2. Perform data analysis using cloud servers
3. Return the integrated results

Resource Analysis

# Example: Automatically process resource files
User: "Analyze the contents of /path/to/document.pdf"

# The system automatically executes:
1. Identify the file type
2. Extract content information
3. Generate a summary through an AI model
4. Return an intelligent summary

📚 Documentation

Troubleshooting

Common Issues and Solutions

1. Connection Issues

   Error: Could not connect to MCP server
   

   • Check the network connection.
   • Ensure the server is started.
   • Check the firewall settings.

2. Authorization Errors

   Error: Invalid API key
   

   • Verify the validity of the API key.
   • Check the key configuration.
   • Contact the administrator to reset the key.

📄 Project Links

• GitHub Repository: https://github.com/Abiorh001/mcp_omni_connect
• Official Documentation: https://mcp-omni.readthedocs.io

🤝 Contribution Guidelines

Welcome contributions from the community!

• Submit an issue to report a problem.
• Submit a PR to fix bugs or add features.
• Participate in the discussion area to discuss solutions.