Fulcra Context MCP

Processes raw sleep data samples into sleep cycles by finding gaps in the sleep sample data within a specified time interval. Result timestamps will include time zones. Always translate timestamps to the user's local time zone when this is known. Args: start_time: The starting timestamp (inclusive), as an ISO 8601 string or datetime object. end_time: The ending timestamp (exclusive), as an ISO 8601 string or datetime object. cycle_gap: Optional. Minimum time interval separating distinct cycles (e.g., "PT2H" for 2 hours). Defaults to server-side default if not provided. stages: Optional. Sleep stages to include. Defaults to all stages if not provided. gap_stages: Optional. Sleep stages to consider as gaps in sleep cycles. Defaults to server-side default if not provided. clip_to_range: Optional. Whether to clip the data to the requested date range. Defaults to True. Returns: A JSON string representing a pandas DataFrame containing the sleep cycle data.

{ "properties": { "clip_to_range": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": true, "title": "Clip To Range" }, "cycle_gap": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "Cycle Gap" }, "end_time": { "format": "date-time", "title": "End Time", "type": "string" }, "gap_stages": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Gap Stages" }, "stages": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Stages" }, "start_time": { "format": "date-time", "title": "Start Time", "type": "string" } }, "required": [ "start_time", "end_time" ], "type": "object" }