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robcerda

Oura MCP Server

by robcerda

get_daily_summary

Retrieve daily Oura summaries covering sleep, readiness, activity, stress, recovery, SpO2, resilience, and temperature. Use it to review how your health metrics changed over a date range.

Instructions

Get one record per day combining the headline numbers: sleep, readiness and activity scores, steps and calories, stress and recovery time, SpO2, resilience level, temperature deviation, and the main sleep period (bedtime, durations, efficiency, HRV, heart rate). Durations are in seconds.

The best starting point for questions like "how have I been sleeping" or "how was my week". Collections the session has no scope for are listed under 'unavailable' and the rest are still returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoLast day to include (inclusive), YYYY-MM-DD. Defaults to today.
start_dateNoFirst day to include, YYYY-MM-DD. Defaults to 6 days before end_date.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It usefully discloses that durations are in seconds and that unavailable collections appear as 'unavailable' while other data is still returned. However, it does not mention auth requirements, read-only safety, or any other side-effect/availability caveats, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose. The metric list is long but necessary for a summary tool, and the second sentence adds usage guidance plus an important edge-case behavior without repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool aggregates many metrics and already has an output schema, the description covers the essential context: cardinality (one record per day), included metrics, duration units, and partial-data behavior. It could mention authentication or fallback behavior, but it is largely complete for an agent to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: both start_date and end_date already have clear explanations of format and defaults. The description does not add parameter-specific semantics beyond the schema, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get one record per day combining the headline numbers'. It enumerates the included metrics, distinguishing this aggregated summary from the many sibling daily-getter tools without needing to open any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'The best starting point for questions like "how have I been sleeping" or "how was my week"' gives clear contextual guidance for when to prefer this tool. It does not explicitly name alternative tools or state when not to use it, so it stops short of a full when/when-not explanation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.