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MNE-MCP server

by Exekiel179·io.github.Exekiel179/mne-mcp·v0.2.2·8 stars
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MNE-Python neurophysiology analysis (EEG, MEG, sEEG, ECoG, fNIRS) via the Model Context Protocol

A85/100grade A
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Safety scan
A85/100

full report

Adoption
Growing

8 stars280 downloads/wk

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MNE-MCP tools (38, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • mne_apply_ica
  • mne_apply_inverse
  • mne_average_evoked
  • mne_check_status
  • mne_compute_noise_cov
  • mne_connectivity
  • mne_crop

    Crop a Raw/Epochs/Evoked object to the time window [tmin, tmax] seconds, in place.

  • mne_decode
  • mne_describe

    Show a detailed summary of one named session object (channels, sfreq, montage, bads, etc.).

  • mne_events_from_annotations

    Convert a Raw object's annotations into an events array + event_id map (for EDF/BrainVision/EEGLAB data).

  • mne_filter
  • mne_find_events

    Find stimulus/trigger events on a stim channel of a Raw object. Stores them under events_name.

  • mne_fit_ica
  • mne_get_config
  • mne_get_info

    Show the full channel list and measurement info for a named session object.

  • mne_interpolate_bads

    Interpolate currently-marked bad channels using spherical splines (requires a montage).

  • mne_list_files
  • mne_load_raw
  • mne_make_epochs
  • mne_make_forward
  • mne_mark_bad_channels
  • mne_plot_epochs_image

    Plot an ERP image (epochs × time heatmap) for an Epochs object. Returns PNG path(s).

  • mne_plot_evoked

    Plot an Evoked response. style: 'joint' (butterfly + topomaps, default), 'topo', or 'butterfly'. Returns PNG path.

  • mne_plot_ica_components

    Plot ICA component scalp topographies (to identify eye/heart/muscle artifacts). Returns PNG path(s).

  • mne_plot_ica_sources

    Plot ICA component time courses for an instrument (raw/epochs). Returns a PNG path.

  • mne_plot_psd

    Plot the power spectral density of a Raw/Epochs/Evoked object. Returns a PNG path.

  • mne_plot_raw

    Plot raw signal traces (a window of channels over time). Returns a PNG path.

  • mne_plot_sensors

    Plot the sensor/electrode layout (kind='topomap' 2D or '3d'). Returns a PNG path.

  • mne_plot_source_estimate
  • mne_plot_topomap

    Plot scalp topographies of an Evoked at given times. times='auto', 'peaks', or comma-separated seconds (e.g. '0.1,0.2,0.3'). Returns PNG path.

  • mne_resample

    Resample a Raw/Epochs object to a new sampling frequency (Hz), in place.

  • mne_reset_session

    Clear all loaded objects and figures from the session, starting fresh. Irreversible.

  • mne_run_codewrite action
  • mne_save
  • mne_session_info
  • mne_set_montage
  • mne_set_reference
  • mne_tfr_morlet

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

1 medium
  • Code scan14 source files scanned20/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 6 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (1)

  • mediumeval / new Function usedexec.eval
    mne_mcp-0.2.2/src/mne_mcp/kernel.py: …one: result_value = eval( compile(ast.Exp…
Overall 85/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How MNE-MCP compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
85/100
higher than 73% of 4,460 AI and agents servers
Tools
38
the typical AI and agents server has 6
Tools that change things
3%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
8
more than 82% of 2,711 AI and agents servers
Downloads a week
280
more than 79% of 1,538 AI and agents servers with a package

What its tools let an agent do: 37 read · 1 change

Install MNE-MCP in Claude Code, Cursor or VS Code

claude mcp add mne-mcp -- uvx mne-mcp
Add to Cursor

What the publisher says

From the MNE-MCP repository's README, as published. We do not edit it. Read it on GitHub

<!-- mcp-name: io.github.Exekiel179/mne-mcp -->

MNE-MCP

English | 简体中文

A Model Context Protocol (MCP) server that gives AI assistants direct, conversational access to MNE-Python for analyzing human neurophysiology data — EEG, MEG, sEEG, ECoG, and fNIRS.

Describe your analysis in plain language — MNE-MCP loads your recording, runs the MNE pipeline (filtering, ICA, epoching, ERP/ERF averaging, time-frequency, source-level work via code), saves the figures, and explains the results.

Works in Claude Code, Codex, PsyClaw and opencode. Pairs with bundled

Agent Skills — mne-analyst, mne-mcp-guard, plus a skeptical analysis suite

(mne-methodology-critic + per-category skills) for reliable, archived workflows.

Why an MCP for MNE-Python?

MNE analysis is stateful and visual — unlike a one-shot statistics batch job:

time-frequency, each step mutating large in-memory objects. MNE-MCP keeps one persistent session so recordings never get re-loaded between steps.

  • You load a Raw recording once, then filter → re-reference → fit ICA → epoch → average →

tool saves a PNG the assistant can read and interpret.

  • Every decision is driven by looking (PSD, sensor maps, ICA components, ERPs). Every plotting

pipeline and advanced analysis (source localization, connectivity, decoding), plus an mneruncode escape hatch that reaches the entire MNE API in the same live session.

  • MNE has a large Python API. MNE-MCP gives you 41 structured tools spanning the common

dirs, timeout) are user-configurable via an interactive mne-mcp configure wizard.

  • Defaults (line frequency, montage, filter band, rejection threshold, ICA settings, epoch window,

Requirements

  • Python 3.12+ (no package upper-version gate; full-test baseline: 3.12)
  • Git
  • Claude Code, Codex, PsyClaw, opencode, or another MCP client

Cross-platform: unlike a closed engine, MNE-Python is pure Python, so analysis tools work on

Windows, macOS, and Linux.

Installation

Looking for the separate native C++ preview? See MNE-CPP MCP installation and capabilities. It now includes explicit native-runtime setup and companion-skill registration; it is not a replacement for the MNE-Python analysis backend described here.

Install with your agent

Send this to a coding agent with terminal access:

Follow https://github.com/Exekiel179/MNE-MCP/blob/v0.4.4/INSTALL_AGENT.md to install MNE-MCP and all companion skills in my existing MNE environment, configure my current client, and verify the result.

The agent checks the environment, installs missing MNE/core libraries when needed, installs the lightweight interface and all 14 skills, and registers the selected client. A client restart is required. See the installation guide for environment checks and verification.

Manual installation

Activate your existing Python 3.12+ MNE environment, then install the lightweight interface:

python -m pip install mne-mcp
mne-mcp setup

The installation creates the mne-mcp command (mne-mcp.exe on Windows). python -m mne_mcp setup remains an equivalent diagnostic invocation.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

MNE-MCP: common questions

Is MNE-MCP server safe?
Yes, by our scan: it is graded A (85/100). Read the MNE-MCP safety report
How do I install MNE-MCP?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does MNE-MCP need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is MNE-MCP maintained?
The last commit was 44 days ago (2026-09-21). The latest release is v0.2.2.
What can I use instead of MNE-MCP?
Servers from other publishers that do the same job: MCP Server for WinDbg Crash Analysis, Stata MCP server and Depwire MCP server.
How does MNE-MCP compare with other AI and agents MCP servers?
safety score 85/100 (higher than 73% of 4,460 AI and agents servers); tools 38 (the typical AI and agents server has 6); tools that change things 3% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to MNE-MCP

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    A
  • Stata
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  • Depwire
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    B