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robcerda

Oura MCP Server

by robcerda

get_workouts

Retrieve workouts by date range, including activity type, start/end times, calories, distance, intensity, and source. Use it to query Oura activity data for analysis or display.

Instructions

Get workouts, auto detected or entered by the user: activity type, start and end time, calories, distance (meters), intensity, and source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoLast day to include (inclusive), YYYY-MM-DD. Defaults to today.
next_tokenNoContinue a truncated result: pass the next_token from the previous response along with the same dates.
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

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that results include both auto-detected and user-entered workouts and lists the returned fields, but it omits behavior such as pagination via next_token, authorization requirements, and the default date range behavior (which is only implied by the schema).

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

Conciseness5/5

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

The description is a single compact sentence with no filler. It front-loads the action ('Get workouts') and immediately provides the useful scope details.

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

Completeness3/5

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

For a simple three-parameter endpoint with a complete schema and an output schema, the description is mostly sufficient, but it lacks usage differentiation among the large sibling set and does not state the authentication or pagination context. An agent could call it correctly from the schema, yet would rely on inference for when to choose it.

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%, so the schema already documents start_date, end_date, and next_token. The description does not add any parameter-level detail beyond this baseline; it only outlines result contents.

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

Purpose4/5

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

The description opens with the specific verb-resource pair 'Get workouts' and enumerates the returned data fields (activity type, times, calories, distance, intensity, source). It is clear, though it does not explicitly distinguish get_workouts from sibling tools like get_sessions or get_daily_activity.

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

Usage Guidelines2/5

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

No guidance is given about when to call this tool rather than alternatives. The phrase 'auto detected or entered by the user' clarifies the data source but does not say when to choose get_workouts over get_sessions or the daily summary tools.

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