Hevy MCP Pro

get_exercise_progression

Track exercise progression with a chronological series of best sets per session, including weight, reps, volume, and estimated 1RM. Optionally set a start date.

Instructions

Return a chronological time series of the best set per session for one exercise template. Uses /v1/exercise_history (single API call). Each point includes weight, reps, volume, and Epley-estimated 1RM. Optional since (ISO 8601) defaults to 90 days ago.

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": {
      "exerciseTemplateId": "<exerciseTemplateId>"
    },
    "name": "get_exercise_progression"
  }
}

Input Schema

Name	Required	Description	Default
`since`	No
`exerciseTemplateId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 10, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the data source, the aggregation logic (best set per session), the Epley formula for 1RM, and the default `since` value. It does not explicitly state whether the operation is read-only, but 'Return' implies it. It also doesn't mention error handling or rate limits, but overall it provides strong behavioral context.

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 three sentences with no filler. It front-loads the core purpose and then adds technical details (API call, output fields, default). Every sentence provides useful information, making it concise and well-structured.

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 there is no output schema and no annotations, the description does a good job of covering what is returned (weight, reps, volume, 1RM), the data source, and the time default. However, it does not define what 'best set' means (e.g., highest 1RM), nor does it describe behavior for empty results or whether the time series is sorted ascending, leaving minor gaps.

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 coverage is 0%, so the description must compensate. It meaningfully explains `since` (format and default), but does not elaborate on `exerciseTemplateId` beyond the phrase 'one exercise template', which is largely a restatement of the parameter name. The description adds some value but leaves room for more explicit parameter documentation.

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 clearly states the specific action ('Return'), the resource ('a chronological time series of the best set per session for one exercise template'), and differentiates from the sibling 'get_exercise_history' by focusing on aggregation and derived 1RM. It is both specific and unambiguous.

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 description provides clear context: it aggregates exercise history into a progression timeline and mentions it uses a single API call (efficiency). However, it does not explicitly name alternatives or state when NOT to use this tool, so it lacks a direct exclusionary guideline.

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