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oura-mcp-local

oura-mcp-local

by ktortti
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

oura_event_context

Retrieve sleep and physiology context for a timed event (test, flight, race): preceding night's sleep, hours awake, HR trough, readiness, and temperature deviation to interpret performance.

Instructions

Sleep and physiology context for a timed event on a given day (a test, a flight, a race): the preceding night (bedtime, wake, duration, lowest HR and when), hours awake at the event, hours since the nightly HR trough, sleep vs 30-day median, readiness and temperature deviation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "date": "<date>",
      "time": "<time>"
    },
    "name": "oura_event_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
dateYesEvent date, YYYY-MM-DD
timeYesLocal clock time of the event, HH:MM

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It does well, listing the exact physiology and sleep metrics it computes: preceding night's bedtime, wake time, duration, lowest HR, hours awake at the event, hours since HR trough, sleep vs 30-day median, readiness, and temperature deviation. It does not mention side effects, but the tool appears read-only; the main missing piece is edge-case behavior such as absence of prior data.

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 a single sentence with a front-loaded purpose ('Sleep and physiology context for a timed event on a given day') followed by a colon-separated list of output dimensions. It is compact and information-dense, with each clause reinforcing the tool's utility. The event examples are short and illustrative, not padding.

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?

Given there is no output schema, the description must cover return values, and it does provide an enumerated list of outputs. However, it does not describe the output structure (e.g., object shape, units, or exact field names) nor how to handle edge cases like an event before bedtime or missing sleep data. It is a reasonable overall picture, but several runtime details for consuming the result remain absent.

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

Parameters4/5

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

Schema coverage is 100%, so the semantic baseline is 3. The description adds value beyond the schema by explaining how date and time are used together, framing them as the event anchor against which metrics like 'hours awake at the event' and 'hours since the nightly HR trough' are computed. This goes beyond the schema's simple 'event date' and 'local clock time of the event'.

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 clearly states the tool's purpose: it returns sleep and physiology context for a timed event on a given day, and gives concrete examples (test, flight, race). It is not a tautology and names the domain resource. However, it does not mention how it differs from sibling tools like oura_daily or oura_sleep_periods, so it lacks explicit sibling differentiation.

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

Usage Guidelines3/5

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

The description implies when to use it via examples like 'a test, a flight, a race' and by emphasizing the 'timed event' angle. It does not explicitly state when NOT to use it or compare with alternative sibling tools, so the guidance is inferential rather than prescriptive.

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

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