Intervals.icu MCP Server

get_athlete_summary

Retrieves a training-load summary—fitness, fatigue, form, and totals—for a chosen date range. Use it to review an athlete's training status over any period.

Instructions

Get a training-load summary (fitness/fatigue/form and totals) over a date range.

Note: the underlying endpoint's ``tags`` parameter filters *athletes* (a
coach-facing feature), not activities, so no tag filter is offered here.

Args:
    start_date: Start date in YYYY-MM-DD format (optional, defaults to 30 days ago).
    end_date: End date in YYYY-MM-DD format (optional, defaults to today).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_athlete_summary"
  }
}

Input Schema

Name	Required	Description	Default
`end_date`	No
`start_date`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Nov 2, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations exist, so the description carries the full burden. It discloses the read-only nature implicitly via 'get', the default window (30 days ago → today), and a non-obvious API constraint (the endpoint's tags parameter filters athletes, not activities) that would otherwise cause wrong assumptions. It does not mention auth requirements, rate limits, or athlete-level scoping.

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?

Front-loaded with the purpose in the first line, followed by a scoping caveat, then a tight Args list. Every element earns its place; only a minor redundancy between the opening 'over a date range' and the Args defaults keeps it from a 5.

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?

The tool has only two optional parameters and an output schema, so return values need no explanation; params, defaults, and the notable excluded filter are all covered. The remaining gap is the absence of any signal about performance, limits on range size, or how the summary relates to sibling metrics tools.

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 description coverage is 0%, so the description must compensate entirely, and it does: both parameters are documented with format (YYYY-MM-DD) and default behavior (30 days ago / today). Only edge semantics — such as inclusive/exclusive range handling or format-error behavior — are left unstated.

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?

Opens with a specific verb and resource ('Get a training-load summary') and enumerates the metrics returned (fitness/fatigue/form and totals) plus the date-range scope. An agent can distinguish it from get_wellness_data or get_athlete_power_curves by the metric names, though no sibling is named explicitly.

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 'Note' rules out a tag-based filter, which usefully prevents a call the agent might expect to make, and the Args block establishes sensible defaults when dates are omitted. However, there is no explicit guidance on when to prefer this summary over get_training_readiness, get_wellness_data, or get_athlete_power_curves, so routing is only implied.

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