BCI-MCP is a Brain-Computer Interface server that enables AI systems to receive and process neural signals through the Model Context Protocol. It supports multiple EEG devices (OpenBCI, Emotiv, NeuroSky), provides real-time signal processing with features like bandpass filtering and event detection, and exposes a WebSocket API for streaming brain activity data. The implementation includes tools for device connection, calibration, data recording, and visualization, making it valuable for creating more intuitive human-AI interactions where brain activity can provide additional context to language models.
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Highlight AILists all available EEG devices that can be connected.
Connects to a specified EEG device.
Disconnects from the currently connected EEG device.
Fetches the current brain state metrics including focus, calm, and attention.
Retrieves the power levels of different EEG frequency bands.
Checks the quality of the EEG signal being received.
Returns definitions for the metrics used, such as focus and calm.
Calibrates the EEG device for optimal performance.
Records EEG data for a specified duration to a file.
Begins a neurofeedback session targeting a specific metric and target value.
Retrieves the score from the last neurofeedback session.
Marks a specific event in the EEG data for later analysis.
Provides a summary of the current EEG stream data.
