neuroencoder

endpoint

https://api.neuroencoder.com/mcp

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is neuroencoder live?

Yes — it answered the hub's last check (checked 2h ago). It answered 100% of checks over the last 30 days.

Is neuroencoder free to use?

Partly — some of its tools are open, others need a key or payment.

What tools does neuroencoder have?

8 tools: account, get_sample, create_upload, start_embedding_job, start_sleep_staging_job, list_samples, get_job, get_result_url.

Is neuroencoder safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• list_samples open 2h ago

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

  mcp-tool

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  {
    "type": "object",
    "title": "list_samplesArguments",
    "properties": {}
  }

  arguments 5 lines copy
• get_job auth-required 2h ago

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

  mcp-tool

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  {
    "type": "object",
    "title": "get_jobArguments",
    "required": [
      "job_id"
    ],
    "properties": {
      "job_id": {
        "type": "string",
        "title": "Job Id"
      }
    }
  }

  arguments 13 lines copy
• get_result_url auth-required 2h ago

  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.

  mcp-tool

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  {
    "type": "object",
    "title": "get_result_urlArguments",
    "required": [
      "job_id"
    ],
    "properties": {
      "job_id": {
        "type": "string",
        "title": "Job Id"
      }
    }
  }

  arguments 13 lines copy
• account unknown never probed

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

  mcp-tool

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  {
    "type": "object",
    "title": "accountArguments",
    "properties": {}
  }

  arguments 5 lines copy
• get_sample unknown never probed

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

  mcp-tool

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  {
    "type": "object",
    "title": "get_sampleArguments",
    "required": [
      "name"
    ],
    "properties": {
      "name": {
        "type": "string",
        "title": "Name"
      }
    }
  }

  arguments 13 lines copy
• create_upload unknown never probed

  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.

  mcp-tool

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  {
    "type": "object",
    "title": "create_uploadArguments",
    "required": [
      "filename",
      "bytes"
    ],
    "properties": {
      "bytes": {
        "type": "integer",
        "title": "Bytes"
      },
      "filename": {
        "type": "string",
        "title": "Filename"
      }
    }
  }

  arguments 18 lines copy
• start_embedding_job unknown never probed

  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.

  mcp-tool

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  {
    "type": "object",
    "title": "start_embedding_jobArguments",
    "required": [
      "file_id"
    ],
    "properties": {
      "picks": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Picks",
        "default": null
      },
      "sfreq": {
        "anyOf": [
          {
            "type": "number"
          },
          {
            "type": "null"
          }
        ],
        "title": "Sfreq",
        "default": null
      },
      "file_id": {
        "type": "string",
        "title": "File Id"
      },
      "channel_names": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Channel Names",
        "default": null
      },
      "stride_seconds": {
        "anyOf": [
          {
            "type": "number"
          },
          {
            "type": "null"
          }
        ],
        "title": "Stride Seconds",
        "default": null
      },
      "window_seconds": {
        "type": "number",
        "title": "Window Seconds",
        "default": 30
      }
    }
  }

  arguments 72 lines copy
• start_sleep_staging_job unknown never probed

  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.

  mcp-tool

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  {
    "type": "object",
    "title": "start_sleep_staging_jobArguments",
    "required": [
      "file_id"
    ],
    "properties": {
      "picks": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Picks",
        "default": null
      },
      "units": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Units",
        "default": null
      },
      "file_id": {
        "type": "string",
        "title": "File Id"
      },
      "eeg_channel": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Eeg Channel",
        "default": null
      },
      "eog_channel": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Eog Channel",
        "default": null
      },
      "channel_names": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Channel Names",
        "default": null
      }
    }
  }

  arguments 79 lines copy

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