Plug your brain into any AI — a real Model Context Protocol (MCP) server that streams live EEG brain state (focus, calm, attention) from any EEG
Plug your brain into any AI — a real Model Context Protocol (MCP) server that streams live EEG brain state (focus, calm, attention) from any EEG device into Claude and any MCP client. That is what the bci mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
Real Model Context Protocol server for EEG. Python on the backend. Plug into Claude Desktop, Claude Code, or Cursor.
bci-mcp on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
The server publishes 1 tool. What each one is for:
Troubleshooting — Runtime logs live in the Manufact dashboard under Runtime Logs (not the build log)Configuration is passed through the environment: MCP_AUTH_TOKEN. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
This sits in the monitoring and observability group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Bci's toolset — Troubleshooting — is a fair guide to whether it matches your workflow. It is maintained by enkhbold470; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Troubleshooting | Runtime logs live in the Manufact dashboard under **Runtime Logs** (not the build log). |
{
"mcpServers": {
"bci-mcp-cloud": {
"url": "https://YOUR-SLUG.run.mcp-use.com/mcp"
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| MCP_AUTH_TOKEN | Credential the server authenticates with. | Yes |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.