# BrainFlow Biosensing Boards (pypi · labmcp-brainflow)

MCP server for EEG/EMG/ECG/PPG boards via BrainFlow (OpenBCI, Muse, Neurosity, Unicorn, BrainBit).

- Trust score: 65/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-30

## Components

- pypi · `labmcp-brainflow`: 65/100 (this document), [markdown](https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow.md), [page](https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow)

## Channel facts

- Registry: `pypi`
- Package: `labmcp-brainflow`
- Version: `0.1.2`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-30.

- **Supply Chain Security**: 49/100
  - Malware scan not yet available for this package.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs hatchling.build at install time, a recognised build step with no custom scripting around it.
  - 2 of 20 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 100/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to K-Dense-AI/lab-instrument-mcps).
  - Clear OSI-approved license (Apache-2.0).
  - Actively maintained (last published 3 days ago).
  - Publishes a security disclosure policy (SECURITY.md).
- **Schema Quality & AI Usability**: 73/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 1477 tokens (~123/item across 12 items; 12 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 93/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 76% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - All 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.
  - An AI judge read all 13 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### How do I install the BrainFlow Biosensing Boards MCP server?

BrainFlow Biosensing Boards runs locally as a PyPI package, launched with uvx labmcp-brainflow. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add k-dense-ai-labmcp-brainflow -- uvx labmcp-brainflow
```

### Cursor

```json
{
  "mcpServers": {
    "k-dense-ai-labmcp-brainflow": {
      "command": "uvx",
      "args": [
        "labmcp-brainflow"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "k-dense-ai-labmcp-brainflow": {
      "command": "uvx",
      "args": [
        "labmcp-brainflow"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add k-dense-ai-labmcp-brainflow -- uvx labmcp-brainflow
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "k-dense-ai-labmcp-brainflow": {
      "type": "local",
      "command": [
        "uvx",
        "labmcp-brainflow"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add k-dense-ai-labmcp-brainflow --command uvx --arg labmcp-brainflow
```

### Hermes

```yaml
mcp_servers:
  k-dense-ai-labmcp-brainflow:
    command: "uvx"
    args: ["labmcp-brainflow"]
```

### Netclaw

```json
{
  "McpServers": {
    "k-dense-ai-labmcp-brainflow": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "labmcp-brainflow"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add k-dense-ai-labmcp-brainflow -t stdio -c uvx -a labmcp-brainflow
```

### Other

```json
{
  "mcpServers": {
    "k-dense-ai-labmcp-brainflow": {
      "command": "uvx",
      "args": [
        "labmcp-brainflow"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-28 (score 65, −5)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-27 (score 70, 0)

- [functional] Package version: 0.1.1 → 0.1.2

### 2026-09-26 (score 70)

First indexed and scored.

## MCP tools (12)

### `get_connection_info` (~40 tokens)

Get Connection Info

Report which instrument is connected (identity, address, simulated or real),
whether the server is read-only, and the active safety limits. Call this first.

### `get_command_log` (~46 tokens)

Get Command Log

Return the most recent raw commands sent to / replies received from the
instrument (newest last). Useful for debugging and for recording what was done.

Input parameters:

- `limit` (integer)

Output parameters:

- `result` (array)

### `reconnect` (~35 tokens)

Reconnect

Close and re-open the connection to the instrument (e.g. after it was power
cycled or a cable was re-plugged).

### `list_supported_boards` (~73 tokens)

List Supported Boards

List common BrainFlow boards: the `--option board=` alias, BrainFlow board id, and which
connection detail `--address` must hold (serial port, Bluetooth MAC, IP address or serial number).
Any other BrainFlow BoardIds name or numeric id is accepted too. Does not need a board.

Output parameters:

- `result` (array)

### `get_board_info` (~59 tokens)

Get Board Info

Describe the connected board: channel names by type (EEG/EMG/ECG/EOG share the EXG rows on
most boards), sampling rate, available presets (data buffers) and streaming state.

Input parameters:

- `preset` (string)

Output parameters:

- `backend` (string): BrainFlow version, or the built-in fake board
- `board` (string)
- `board_id` (integer)
- `buffered_samples` (integer)
- `channels` (object): Channel names per type (EXG rows are shared by eeg/emg/ecg/eog)
- `device_name`
- `exg_unit`
- `preset` (string)
- `presets` (array): Data buffers this board provides
- `sampling_rate_hz` (integer)
- `simulated` (boolean)
- `streaming` (boolean)
- `timestamp` (string)

### `start_streaming` (~83 tokens)

Start Streaming

Start continuous acquisition into BrainFlow's ring buffer (the board's radio/LEDs switch on;
nothing is applied to the participant). Needed for `insert_marker`; `record` then reads from
the live stream. Call `stop_streaming` when finished.

Input parameters:

- `buffer_duration_s` (number): Size of BrainFlow's ring buffer, in seconds of data

Output parameters:

- `buffer_duration_s`
- `buffered_samples` (integer)
- `message` (string)
- `sampling_rate_hz` (integer)
- `streaming` (boolean)
- `timestamp` (string)

### `stop_streaming` (~56 tokens)

Stop Streaming

Stop acquisition (saves battery). A `record` in progress ends at once with the data acquired
so far. Data already in the buffer is kept until the next stream starts or the session is
released (`reconnect`).

Output parameters:

- `buffer_duration_s`
- `buffered_samples` (integer)
- `message` (string)
- `sampling_rate_hz` (integer)
- `streaming` (boolean)
- `timestamp` (string)

### `record` (~206 tokens)

Record

Record `duration_s` seconds and return per-channel statistics, event markers and downsampled
traces. Uses the live stream if one is running, otherwise starts a temporary one. The full data
(every row, full sampling rate) can be written to `save_path`. `stop_streaming` ends a recording
early.

Input parameters:

- `channel_type` (string): Which channels to summarise
- `duration_s` (number): Seconds of data to collect
- `include_traces` (boolean): Return downsampled traces
- `max_points` (integer): Max points per downsampled trace
- `preset` (string)
- `remove_dc` (boolean): Subtract each channel's mean from the traces
- `save_format` (string): csv: labelled columns; brainflow: DataFilter.write_file format (replayable)
- `save_path`: Write the full-resolution data (all rows) to this new file (.csv; never overwrites a file)

Output parameters:

- `board` (string)
- `channels` (array)
- `duration_s` (number)
- `end_time`
- `markers` (array)
- `n_samples` (integer)
- `preset` (string)
- `sampling_rate_hz` (integer)
- `saved_format`
- `saved_to`
- `simulated` (boolean)
- `start_time`
- `stopped_early` (boolean): True if stop_streaming ended the recording early: the data covers only the time before it
- `timestamp` (string)
- `trace_times_s`: Time axis of the downsampled traces
- `traces`: Downsampled traces per channel
- `traces_dc_removed` (boolean)

### `get_band_powers` (~122 tokens)

Get Band Powers

EEG band powers (delta 1-4, theta 4-8, alpha 8-13, beta 13-30, gamma 30-50 Hz) over the most
recent `window_s` seconds: BrainFlow's channel-averaged relative powers plus per-channel absolute
(uV^2) and relative powers and the peak frequency. Records a fresh window if not streaming.

Input parameters:

- `channel_type` (string): EXG channel group to analyse
- `window_s` (number): Seconds of data to analyse (4 s recommended)

Output parameters:

- `average_relative` (object): BrainFlow DataFilter.get_avg_band_powers: channel-averaged, relative (sums to 1)
- `average_relative_stddev` (object): Across-channel stddev / mean per band
- `bands_hz` (object)
- `board` (string)
- `channels` (array)
- `processing` (string)
- `sampling_rate_hz` (integer)
- `simulated` (boolean)
- `timestamp` (string)
- `window_s` (number)

### `get_signal_quality` (~83 tokens)

Get Signal Quality

Check every EXG channel for common electrode problems: flat line (disconnected), railed
(amplifier saturated, OpenBCI Cyton boards), strong 50/60 Hz mains noise (poor contact or
missing reference), and implausibly high amplitude (movement, muscle, loose electrode).

Input parameters:

- `window_s` (number): Seconds of data to assess

Output parameters:

- `advice` (string)
- `board` (string)
- `channels` (array)
- `dominant_mains_hz`
- `sampling_rate_hz` (integer)
- `simulated` (boolean)
- `summary` (object)
- `timestamp` (string)
- `window_s` (number)

### `insert_marker` (~80 tokens)

Insert Marker

Write an event marker into the data stream at the current sample (for event-related
experiments: stimulus onsets, condition changes). Requires `start_streaming`; markers appear in
\`record` results and saved files.

Input parameters:

- `preset` (string)
- `value` (number, required): Event code written to the marker channel; must not be 0

Output parameters:

- `message` (string)
- `timestamp` (string)
- `value` (number)

### `configure_board` (~149 tokens)

Configure Board

Send a raw board-specific command to the firmware through BrainFlow's config_board (e.g.
OpenBCI channel settings 'x1060110X', test signals, or Muse presets 'p50'/'p61' to enable PPG).

The string is passed through unchecked: besides acquisition settings, some commands switch on
outputs such as the lead-off (impedance-test) current that flows through the participant's
electrodes. Settings persist until another command changes them or the board is power-cycled
(stopping the stream does not undo them). Consult the board's SDK documentation first and tell
the user what the command does.

Input parameters:

- `command` (string, required): Board-specific configuration string

Output parameters:

- `command` (string)
- `reply` (string)
- `timestamp` (string)

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow#diagnostics

## Score history

- 2026-09-30: 65
- 2026-09-29: 65
- 2026-09-28: 65
- 2026-09-27: 70
- 2026-09-26: 70

## Common questions

### What is the BrainFlow Biosensing Boards MCP server?

BrainFlow Biosensing Boards is an MCP server listed in the public MCP registry as io.github.K-Dense-AI/labmcp-brainflow. MCP server for EEG/EMG/ECG/PPG boards via BrainFlow (OpenBCI, Muse, Neurosity, Unicorn, BrainBit). This page covers its PyPI package (labmcp-brainflow).

### Is the BrainFlow Biosensing Boards MCP server safe to use?

BrainFlow Biosensing Boards scores 65 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 30 September 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the BrainFlow Biosensing Boards MCP server expose?

BrainFlow Biosensing Boards exposes 12 tools: get_connection_info, get_command_log, reconnect, list_supported_boards, get_board_info, and 7 more. Their descriptions and schemas cost roughly 1,032 tokens of context every time the server is loaded.

### Is the BrainFlow Biosensing Boards MCP server still maintained?

BrainFlow Biosensing Boards is still listed as active in the MCP registry. We last reached this channel on 30 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the BrainFlow Biosensing Boards MCP server under?

BrainFlow Biosensing Boards declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- PyPI project: https://pypi.org/project/labmcp-brainflow/
- Socket report: https://socket.dev/pypi/package/labmcp-brainflow
- Repository: https://github.com/K-Dense-AI/lab-instrument-mcps
- Website: https://github.com/K-Dense-AI/lab-instrument-mcps/tree/main/servers/health/brainflow-biosensors
- Changelog RSS feed: https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow.xml
- Changelog JSON feed: https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow.json
- HTML version of this page: https://verifymcp.io/servers/k-dense-ai-labmcp-brainflow/labmcp-brainflow