MNE-MCP (Exekiel179/MNE-MCP) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 39 tools. No publisher has claimed this listing.

Emerging

74/100

MNE-MCP

Item: MNE-MCP
Rating: 74
Author: M8ven

An 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.

→ Exekiel179/MNE-MCP · listed on glama

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

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Who stands behind it

Exekiel179

Source: Glama

Is this your MCP?

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Install from

Glamanot scored here

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings

✅

No credential exfiltration, no sensitive file access, no obfuscation

Static analysis found nothing flowing your secrets to unexpected places.

✅

Open source with a license and README

Anyone can audit the code, the license is declared, and the publisher documents what it does.

// tools this server exposes39 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

mne_check_status

mne_install_backend

mne_get_config

mne_session_info

mne_describe

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

mne_get_info

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

mne_reset_session

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

mne_run_code

mne_list_files

mne_load_raw

mne_filter

mne_resample

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

mne_crop

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

mne_set_montage

mne_set_reference

mne_mark_bad_channels

mne_interpolate_bads

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

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_fit_ica

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_apply_ica

mne_find_events

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

mne_events_from_annotations

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

mne_make_epochs

mne_plot_epochs_image

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

mne_average_evoked

mne_plot_evoked

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

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_tfr_morlet

mne_save

mne_decode

mne_connectivity

mne_compute_noise_cov

mne_make_forward

mne_apply_inverse

mne_plot_source_estimate

// environment variables

To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.

configMNE_MCP_CLAUDE_CONFIG

configMNE_MCP_CODEX_CONFIG

configMNE_MCP_OPENCODE_CONFIG

configMNE_MCP_CONFIGDefaults are saved to ~/.mne-mcp/config.json (override path with ). Precedence at

configMNE_MCP_TIMEOUT

configMNE_MCP_DATA_DIR

configMNE_MCP_TEMP_DIR

configMNE_MCP_RESULTS_DIR

// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

39/39 tools missing one or more hints — mne_check_status (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); mne_install_backend (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); mne_get_config (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +36 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tool test coverage

Only 9/39 tools referenced in tests (23%)

Write tests that reference each tool by name so every tool has at least one test.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail

The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.

// improvement guidance — verified publishers only

We have 3 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

// embed badge in your README

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commit: 627142cb5beebe1a210a8e0fb1e15afbec8b8010

code hash: c643aee775e2e003225f0ed7f92ae1c4641e18229fc905b163ac8c5695a6fe78

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