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Neuroencoder EEG embeddings

by com.neuroencoder
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Server Details

Hosted EEG embeddings API: any montage and sampling rate, EDF/BDF/FIF/NPY, 768-d vector per window

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Status
Healthy
Uptime
100.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
ChatGPT
–
Claude
–

TDQS

A3.7/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: account info, file upload, job status, result retrieval, sample listing/detail, and two domain-specific job starters. The two start_*_job tools are differentiated by embeddings vs sleep staging, so an agent can select correctly from names and descriptions.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern: create_upload, get_job, get_result_url, get_sample, list_samples, start_embedding_job, start_sleep_staging_job. The lone noun-style name 'account' is a minor deviation but remains clear.

Tool Count5/5

Eight tools are well scoped for an EEG embedding/sleep-staging workflow, covering upload, job orchestration, results, and sample exploration. Each tool earns its place without excessive surface area.

Completeness4/5

The core lifecycle is covered: account check, upload, queue embeddings or sleep staging, poll status, retrieve results, and inspect samples. Minor gaps exist around job management, such as no explicit cancel_job, delete_upload, or list_jobs operation, though these are not required for the primary workflow.

Available Tools

8 tools
accountBInspect

This API key: tier, limits and usage this month.

Inputs: no named parameters.

create_uploadAInspect

Start an upload of a local .edf, .bdf or .npy file (at most 2 GB). Returns id and a presigned upload_url: PUT the file there within 10 minutes with exactly upload_headers (e.g. curl -X PUT --upload-file night.edf -H 'Content-Length: N' '<upload_url>', no Authorization header), then call start_embedding_job with the id. Only the extension of filename is used.

Inputs: bytes (required), filename (required).

get_jobAInspect

A job's status (queued, running, succeeded, failed, cancelled, expired), usage, error or result. Poll every 5 s while queued or running.

Inputs: job_id (required).

get_result_urlAInspect

Fresh presigned GET URLs (10 minutes) of a succeeded job's result. Embeddings: .npy float32 [windows, 768], window i starts at i * t_start_step s. Sleep staging: url = hypnogram JSON (stage, probabilities, confidence per 30 s epoch), csv_url = CSV, plus the summary.

Inputs: job_id (required).

get_sampleBInspect

One sample: README, licence, channels_used, and its embeddings in the POST /v1/embeddings response format (first windows only for long ones).

Inputs: name (required).

list_samplesCInspect

Precomputed real outputs (no upload needed): ids, titles, sizes, download URLs.

Inputs: no named parameters.

start_embedding_jobAInspect

Queue an embeddings job on an uploaded file. window_seconds: 2 to 30 (default 30); stride_seconds: default window_seconds. picks: EDF/BDF channel labels to keep; channel_names: 10-20 labels overriding the file's; sfreq: required for .npy. Bills 30 s of EEG per window at any window_seconds (refunded on failure). Poll get_job.

Inputs: file_id (required), picks, sfreq, channel_names, +2 more.

start_sleep_staging_jobAInspect

Queue sleep staging of an uploaded whole-night PSG (.edf/.bdf; >= 1 EEG channel with a 10-20 label at >= 100 Hz; EOG used if present). eeg_channel/eog_channel: channels for the YASA features; picks, channel_names as for embeddings. Counts 1 night of the weekly quota (refunded on failure). Poll get_job, then get_result_url. Research use only, not a medical device.

Inputs: file_id (required), picks, units, eeg_channel, +2 more.

Tool Schema Changelog

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