openbci-mcp
Related Servers
Alternatives to openbci-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceA Model Context Protocol server that provides AI agents with a unified interface for real-time EEG acquisition, replay, processing, visualization, recording, and stimulation from over 66 BrainFlow boards.472BSD 3-Clause
- AlicenseNot gradedqualityCmaintenanceAn MCP server that gives AI agents a unified interface to clinical/research EEG workflows: signal processing, source imaging, persistent dataset/EHR storage, and web visualization.84 PyPI1BSD 3-Clause
- AlicenseNot gradedqualityDmaintenanceMCP server for controlling compatible boards over Bluetooth serial, including DC motors, servos, IO, and sensors.MIT
- AlicenseBqualityCmaintenanceAn MCP server that gives AI assistants conversational access to MNE-Python for analyzing neurophysiology data (EEG, MEG, sEEG, ECoG, fNIRS). Enables plain-language analysis pipelines, from loading recordings to generating figures and explanations.4173 PyPI10MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents and humans to control various hardware boards (ESP32, Arduino, Raspberry Pi, etc.) through a unified API via MCP, with real-time dashboard support.MIT
- AlicenseNot gradedqualityDmaintenanceA Model Context Protocol (MCP) server for seamless integration with peripheral devices connected to your computer. Control, monitor, and manage hardware devices through a unified API.5MIT
TDQS
Scored across 7 tools
Each tool targets a distinct aspect of OpenBCI operation: board management, streaming, signal analysis, export, triggers, help, and high-level workflow orchestration. No two tools have overlapping primary purposes.
Most tools follow the pattern 'openbci_<function>', all lowercase with underscores. However, 'agentic_openbci_workflow' deviates with the prefix 'agentic', and 'openbci_help' is a noun instead of a verb, slightly breaking consistency.
With 7 tools, the server covers the essential functions for BCI data acquisition and processing without being bloated. Each tool has a clear role, and the count feels well-scoped for the domain.
The core workflow (connect, stream, analyze, export, trigger) is fully covered. Minor gaps exist, such as lacking advanced signal processing (e.g., artifact removal, epoch extraction) and hardware configuration details, but the set is sufficient for typical use cases.