Brain-Computer Interface with Model Context Protocol¶

Welcome to the documentation for BCI-MCP, an integration of Brain-Computer Interface (BCI) technology with the Model Context Protocol (MCP) for advanced neural signal acquisition, processing, and AI-enabled interactions.

Overview¶

BCI-MCP combines the power of:

Brain-Computer Interface (BCI): Real-time acquisition and processing of neural signals
Model Context Protocol (MCP): Standardized AI communication interface

This integration enables a wide range of 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

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

Getting Started¶

To start using BCI-MCP, check out our Quick Start Guide.

Architecture¶

The BCI-MCP system consists of several key components:

┌─────────────────┐      ┌─────────────────┐      ┌─────────────────┐
│                 │      │                 │      │                 │
│  BCI Hardware   │──────│  BCI Software   │──────│   MCP Server    │
│                 │      │                 │      │                 │
└─────────────────┘      └─────────────────┘      └────────┬────────┘
                                                           │
                                                           │
                                                  ┌────────▼────────┐
                                                  │                 │
                                                  │  AI Applications │
                                                  │                 │
                                                  └─────────────────┘

Documentation Status¶

This documentation is automatically built and deployed using GitHub Actions when changes are made to the main branch.

Contributing¶

We welcome contributions from the community! Check out our Contributing Guide to learn how you can help.

License¶

This project is licensed under the MIT License - see the LICENSE file in the repository for details.

New Update (2025-03-23)¶

This is a test update to trigger the documentation workflow. The documentation should be automatically deployed to GitHub Pages.