TrainingPeaks MCP

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tp_get_peaks

Retrieve top performances for Bike or Run by PR type (e.g., 1-min power, 5K speed) and compare personal records over time. Supports optional date range and athlete filtering.

Instructions

Get top performances by type. For comparing PRs over time.

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": {
      "sport": "<sport>",
      "pr_type": "<pr_type>"
    },
    "name": "tp_get_peaks"
  }
}

Input Schema

Name	Required	Description
`days`	No
`sport`	Yes
`athlete`	No	Target athlete name or ID (coach accounts only). Omit to use your own profile.
`pr_type`	Yes	Bike: power1min/5min/20min. Run: speed5K/10K/Half

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Jul 31, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. 'Get' implies a read-only operation, and the description adds no hidden side effects, but it does not disclose return format, auth requirements, or scope behavior beyond what the schema suggests. This is adequate for a simple read tool but not richly transparent.

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?

Two short sentences, front-loaded with the action and resource, with no wasted words. Every phrase earns its place.

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?

The tool has no output schema or annotations, and the description does not specify the return structure or the interaction between days, sport, pr_type, and athlete. It is sufficient for basic invocation because required params are in the schema, but it leaves ambiguity about the exact output and filtering behavior.

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

Parameters2/5

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

Schema coverage is only 50%, with no descriptions for 'sport' or 'days'. The description's 'by type' loosely maps to pr_type but adds no value beyond the existing schema description for pr_type and does not compensate for the undocumented parameters.

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 gets top performances by type, and the phrase 'For comparing PRs over time' adds a specific use case. It is distinct from siblings like tp_get_workout_prs by focusing on type-based peak values, though it does not explicitly name an alternative.

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?

'For comparing PRs over time' offers a clear context for when to use this tool. It does not list exclusions or explicitly mention alternatives, but the intended use case is evident enough for an agent to decide.

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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