Omnimcp

🚀 OmniMCP Project Documentation

OmniMCP is a comprehensive project aiming to achieve multi - modal understanding and intelligent operations in human - machine interaction. This project combines natural language processing, computer vision, and robotics to enable end - to - end control of complex tasks.

🚀 Quick Start

OmniMCP integrates multiple sensor data for real - time analysis, supports multi - language dialogue, and can execute complex tasks through robotic arms or virtual assistants.

Installation

1. Clone the project repository:

   git clone https://github.com/OpenAdaptAI/OmniMCP.git
   cd OmniMCP
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Start the service:

   python main.py
   

Usage

1. Configuration file: Edit config.json to configure sensors and operating devices.
2. Start the service: Run the main program and access the Web interface for control.

✨ Features

• OmniMCP Architecture: Integrate multiple sensor data (such as images and voices) for real - time analysis.
• Natural Language Interaction: Support multi - language dialogue, understand context and generate corresponding responses.
• Intelligent Operations: Execute complex tasks through robotic arms or virtual assistants.

🔧 Technical Details

1. System Architecture

• Sensor Integration: Integrate cameras, microphones, and other IoT devices.
• Data Processing: Use deep learning models to perform real - time analysis on multi - modal data.
• Decision Engine: Generate operation instructions based on the analysis results.

2. Natural Language Processing

• Multi - language Support: Support voice recognition and text understanding in multiple languages.
• Context Understanding: Provide more intelligent answers through context reasoning.

3. Intelligent Operations

• Robotic Arm Control: Achieve precise control of industrial robotic arms.
• Virtual Assistant Integration: Interact with mainstream virtual assistants (such as ChatGPT).

💻 Usage Examples

Basic Usage

# Initialize an OmniMCP instance
omni = OmniMCP()

# Receive voice commands
command = omni.stt.listen()
print("User command:", command)

# Analyze image data
image_path = "input.jpg"
objects = omni.vision.analyze(image_path)
print("Detected objects:", objects)

# Execute operations
omni.robot.control("grab", object_id=0)

📚 Documentation

Currently, OmniMCP has achieved basic multi - modal data processing and simple task operation functions. It is being developed with more complex scene understanding capabilities and high - precision operation algorithms.

🤝 Contribution Guidelines

1. Issue Reporting: Submit bugs or feature requests through GitHub Issues.
2. Code Contribution: Fork the repository and submit a PR.
3. Documentation Improvement: Provide usage feedback and optimization suggestions.

📄 License

MIT License

📞 Contact Information

• Issues: GitHub Issues
• Discussions: Discussions
• Security: security@openadapt.ai