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Ephys

Read-only analysis of intracortical BCI recordings (NWB, DANDI, WAV): spikes, PSTHs, decoding, plots

Connector by happyc0der · GitHub account verified by the MCP Registry

IndexedCC0-1.0Local (stdio)★ 1
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Read-only analysis of intracortical BCI recordings (NWB, DANDI, WAV): spikes, PSTHs, decoding, plots

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.

Tools
12 read · 1 write · 1 delete · 11 not yet classified
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Tools by what they do 25

Read from the source code; the running server may list different tools.

Read 12 · Look things up without changing anything.

  • detect_spikes
  • evaluate_cross_session
  • get_firing_rates
  • get_probe
  • get_psth
  • get_session_info
  • get_signal_quality
  • get_stream_status
  • list_dataset_files
  • list_lsl_streams
  • list_sources
  • search_datasets

Write 1 · Create, change, send or run things.

  • set_probe_geometry

Delete 1 · Delete, drop, revoke or wipe things.

  • close_session

Not yet classified 11 · We could not tell from the name and description.

  • decode_window
  • fit_decoder
  • fit_latent_factors
  • open_session
  • plot_decoding
  • plot_latent_factors
  • plot_probe
  • plot_psth
  • plot_raster
  • sort_spikes
  • wrapper

Network hosts it talks to 3

  • api.dandiarchive.org · found in code
  • github.com · found in code
  • glama.ai · found in code

Files it touches

  • Your home directory (~)
  • Any path the agent passes to its tools

Tools (25)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

  • close_session

    Close a session and drop any decoder fitted on it.

  • decode_window

    Decode a window with the fitted decoder; returns a downsampled decoded-vs-true preview.

  • detect_spikes

    Threshold-crossing spike detection on a broadband snippet (max 10 s). Where the session has ground-truth spikes, precision and recall are reported.

  • evaluate_cross_session

    Fit a decoder on one session and score it, unchanged, on other sessions: the question benchmarks such as FALCON ask (does a decoder survive to a later day?). All sessions must be open and share the same units/channels. `mask` names a boolean behaviour signal restricting which bins are scored (FALCON files carry `eval_mask`; pass null when the sessions have none). Also reports same-session held-out R² for comparison.

  • fit_decoder

    Fit a decoder from spike counts to a behaviour signal and score it on held-out data. The first `train_fraction` of the session trains; the remainder tests. With no `target`, the first velocity-like behaviour signal is used. Unrecorded gaps are skipped. `mask` names a boolean behaviour signal (such as FALCON's eval_mask); only bins where it is true are used for fitting and scoring.

  • fit_latent_factors

    Fit low-dimensional latent factors to trial-aligned population activity. GPFA (Yu et al. 2009) gives denoised single-trial trajectories and a timescale per factor; PCA is the fast, noisier baseline. Look for an elbow in variance_explained_per_factor to judge dimensionality. If the session has a velocity-like signal, reports how well the top factors explain it. Then plot_latent_factors draws the trajectories.

  • get_firing_rates

    Population firing-rate summary over a time range (defaults to the whole session).

  • get_probe

    Contact geometry and brain-area labels per channel, where known. Use the `channel` indices with the `units` argument of get_psth / fit_latent_factors to analyse one area.

  • get_psth

    Peri-stimulus time histogram: firing aligned to a trial event and averaged over trials. `event` is one of the session's event_columns (default: movement onset if present). `group_by` splits trials by one of its group_columns, e.g. reach direction. `units` restricts the analysis to some units; tuning that cancels in the population average (such as direction preference) only shows up per unit. Unit numbers in the result index into `units` when it is given. Returns the population time course, its peak, and the units that change most.

  • get_session_info

    Metadata for a session: duration, channels, sampling rates, behaviour signals, licence, citation.

  • get_signal_quality

    Noise level, SNR and dead/noisy channels from a broadband snippet (max 10 s).

  • get_stream_status

    For a live session: how much signal is buffered, whether data is still arriving, and drops.

  • list_dataset_files

    Licence, citation and NWB files of a DANDI dataset. Pass a file's path to open_session(source='dandi').

  • list_lsl_streams

    Lab Streaming Layer streams visible on the local network (needs the lsl extra).

  • list_sources

    List the data source types this server can open, with their parameters and status.

Show 10 more tools
  • open_session

    Open a recording session and return its session_id and metadata. `params` overrides the source's default_params (see list_sources).

  • plot_decoding

    Figure: decoded against actual behaviour for a window (max 60 s), one panel per dimension. Requires fit_decoder first. Pick a window in the test split for an honest picture.

  • plot_latent_factors

    Figure: the top three latent factors over time (single trials thin, group means bold), the trajectory in the plane of the first two factors, and variance explained per factor. Requires fit_latent_factors first.

  • plot_probe

    Figure: the array map, each contact coloured by its firing rate over a window, with area labels and sorted units marked when a sort has been run. Needs geometry from the file or set_probe_geometry.

  • plot_psth

    Figure: population PSTH per group (mean ± SEM over trials) above a unit-by-time heatmap of change from baseline. Same arguments as get_psth. Returns the PNG path and the image.

  • plot_raster

    Figure: spike raster for a time window (max 60 s), with unrecorded spans shaded.

  • search_datasets

    Search the DANDI Archive for datasets. An empty query returns a short curated list of intracortical datasets that work well with this server.

  • set_probe_geometry

    Tell the server where the recording's contacts are, for sessions whose file does not say. Named layouts: 'utah' (square grid, e.g. 96 contacts at 400 um), 'grid' with n_columns, 'linear' (one column at pitch_um, e.g. a laminar probe), 'tetrode_linear' (groups of four). 'explicit' takes positions_um as [[x, y], ...] in channel order. Geometry is used by sort_spikes and plot_probe. Contacts under 100 um apart are sorted jointly.

  • sort_spikes

    Spike-sort a broadband window (needs the sort extra). Afterwards the session's spike times are the sorted units, restricted to that window, so rates, PSTHs, rasters and decoders use them. Uses the session's probe geometry (from the file or set_probe_geometry) so nearby contacts are sorted jointly; without geometry each channel is treated as an independent electrode. Sorting takes seconds to a few minutes depending on duration and channel count.

  • wrapper

Signals

Stars
1
Forks
0
Open issues
1
Weekly downloads
62
Last commit
Sep 25, 2026 (1 month ago)
Last release
Sep 22, 2026 (1 month ago)
Last package publish
Sep 22, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name
io.github.happyc0der/ephys-mcp
Version
0.5.1
Auth
No auth
Packages
pypi ephys-mcp
License
CC0-1.0
Repository
github.com/happyc0der/ephys-mcp
Website
github.com/happyc0der/ephys-mcp
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
Official MCP Registrygithub-graphql

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Ephys MCP server. Agent Mart. https://agentmart.dev/connectors/happyc0der-ephys-mcp (last updated 2026-10-24)