https://github.com/enkhbold470/bci-mcp
Brain-Computer Interface (BCI) implementation with Model Context Protocol (MCP) for advanced neural signal processing and AI integration
https://github.com/enkhbold470/bci-mcp
Last synced: about 2 months ago
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Brain-Computer Interface (BCI) implementation with Model Context Protocol (MCP) for advanced neural signal processing and AI integration
- Host: GitHub
- URL: https://github.com/enkhbold470/bci-mcp
- Owner: enkhbold470
- Created: 2025-03-23T11:01:47.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-03-23T12:27:07.000Z (6 months ago)
- Last Synced: 2025-04-24T00:58:34.882Z (5 months ago)
- Language: Python
- Homepage: https://enkhbold470.github.io/bci-mcp/
- Size: 713 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
Awesome Lists containing this project
- awesome-mcp-servers - **bci-mcp** - Brain-Computer Interface (BCI) implementation with Model Context Protocol (MCP) for advanced neural signal processing and AI integration `python` `mcp` `ai` `pip install git+https://github.com/enkhbold470/bci-mcp` (AI/ML)
- awesome-mcp-servers - **bci-mcp** - Brain-Computer Interface (BCI) implementation with Model Context Protocol (MCP) for advanced neural signal processing and AI integration `python` `mcp` `ai` `pip install git+https://github.com/enkhbold470/bci-mcp` (AI/ML)
README
# Brain-Computer Interface with Model Context Protocol (BCI-MCP)
This project integrates Brain-Computer Interface (BCI) technology with the Model Context Protocol (MCP) to create a powerful framework for neural signal acquisition, processing, and AI-enabled interactions.
[](https://enkhbold470.github.io/bci-mcp/)
[](https://opensource.org/licenses/MIT)
## Overview
BCI-MCP combines:
- **Brain-Computer Interface (BCI)**: Real-time acquisition and processing of neural signals
- **Model Context Protocol (MCP)**: Standardized AI communication interface
This integration enables advanced applications in healthcare, accessibility, research, and human-computer interaction.
## Key Features
### BCI Core Features
- **Neural Signal Acquisition**: Capture electrical signals from brain activity in real-time
- **Signal Processing**: Preprocess, extract features, and classify brain signals
- **Command Generation**: Convert interpreted brain signals into commands
- **Feedback Mechanisms**: Provide feedback to help users improve control
- **Real-time Operation**: Process brain activity with minimal delay
### MCP Integration Features
- **Standardized Context Sharing**: Connect BCI data with AI models using MCP
- **Tool Exposure**: Make BCI functions available to AI applications
- **Composable Workflows**: Build complex operations combining BCI signals and AI processing
- **Secure Data Exchange**: Enable privacy-preserving neural data transmission
## System Architecture
The BCI-MCP system consists of several key components:
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ │ │ │ │ │
│ BCI Hardware │──────│ BCI Software │──────│ MCP Server │
│ │ │ │ │ │
└─────────────────┘ └─────────────────┘ └────────┬────────┘
│
│
┌────────▼────────┐
│ │
│ AI Applications │
│ │
└─────────────────┘
```
## Getting Started
### Prerequisites
- Python 3.10+
- Compatible EEG hardware (or use simulated mode for testing)
- Additional dependencies listed in requirements.txt
### Installation
```bash
# Clone the repository
git clone https://github.com/enkhbold470/bci-mcp.git
cd bci-mcp
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
```
### Using Docker
For easier setup, you can use Docker:
```bash
# Build and start all services
docker-compose up -d
# Access the documentation at http://localhost:8000
# The MCP server will be available at ws://localhost:8765
```
### Basic Usage
```bash
# Start the MCP server
python src/main.py --server
# Or use the interactive console
python src/main.py --interactive
# List available EEG devices
python src/main.py --list-ports
# Record a 60-second BCI session
python src/main.py --port /dev/tty.usbmodem1101 --record 60
```
## Advanced Applications
The BCI-MCP integration enables a range of cutting-edge applications:
### Healthcare and Accessibility
- **Assistive Technology**: Enable individuals with mobility impairments to control devices
- **Rehabilitation**: Support neurological rehabilitation with real-time feedback
- **Diagnostic Tools**: Aid in diagnosing neurological conditions
### Research and Development
- **Neuroscience Research**: Facilitate studies of brain function and cognition
- **BCI Training**: Accelerate learning and adaptation to BCI control
- **Protocol Development**: Establish standards for neural data exchange
### AI-Enhanced Interfaces
- **Adaptive Interfaces**: Interfaces that adjust based on neural signals and AI assistance
- **Intent Recognition**: Better understanding of user intent through neural signals
- **Augmentative Communication**: Enhanced communication for individuals with speech disabilities
## Documentation
The project documentation is hosted on GitHub Pages at: [https://enkhbold470.github.io/bci-mcp/](https://enkhbold470.github.io/bci-mcp/)
### Maintaining the Documentation
The documentation is built using MkDocs with the Material theme. To update the documentation:
1. Make changes to the Markdown files in the `docs/` directory on the `main` branch
2. Commit and push your changes to the `main` branch
3. The GitHub Actions workflow will automatically build and deploy the updated documentation to GitHub Pages
### Local Documentation Development
To work with the documentation locally:
1. Install the required dependencies:
```bash
pip install mkdocs-material mkdocstrings mkdocstrings-python
```
2. Run the local server:
```bash
mkdocs serve
```
3. View the documentation at: http://localhost:8000
## Project Structure
```
.
├── docs/ # Documentation files
│ ├── api/ # API Documentation
│ ├── features/ # Feature Documentation
│ ├── getting-started/ # Getting Started Guides
│ └── index.md # Documentation Home Page
├── mkdocs.yml # MkDocs Configuration
└── .github/workflows/ # GitHub Actions Workflows
```
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Acknowledgments
- Inspired by the [OpenBCI](https://openbci.com/) project
- Built on the [Model Context Protocol](https://modelcontextprotocol.io/) framework
- Thanks to the neuroscience and AI research communities
## Contact
Enkhbold Ganbold - [GitHub Profile](https://github.com/enkhbold470)
Project Link: [https://github.com/enkhbold470/bci-mcp](https://github.com/enkhbold470/bci-mcp)