vital_get_workoutsGet workouts summaries for a user over a date range. Vital API: GET /v2/summary/workouts/{user_id}.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | The Vital user id (UUID). | |
| end_date | No | End date yyyy-mm-dd (inclusive). Defaults to today upstream. | |
| provider | No | Filter to a single provider slug (e.g. oura, fitbit). | |
| start_date | Yes | Start date yyyy-mm-dd (inclusive, required). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description reinforces this with the explicit 'GET' method and the 'summary' endpoint path, adding slight context beyond the annotation. However, it does not disclose behavioral details such as pagination, default end_date behavior, timezone handling, or data availability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. It front-loads the action and resource, then adds the precise API endpoint. Every sentence earns its place and the definition is appropriately sized for a simple read-only wrapper.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with complete parameter schema and a read-only annotation, the description is adequate for invocation. However, there is no output schema and the description does not describe the response shape, pagination, or error behavior, so an agent has limited context about what will be returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all four parameters are already documented. The description adds no parameter-level meaning beyond the endpoint referencing {user_id}. This meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Get workouts summaries for a user over a date range.' It identifies the exact API endpoint, which helps an agent understand the operation. However, it does not explicitly distinguish this from sibling tools like vital_get_activity or vital_get_sleep, so it stops short of full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The core use case is implied: use when you need workout summaries for a user over a date range. But there is no explicit statement about when not to use it, no mention of alternatives, and no exclusions relative to the many sibling vital_get_* tools. Usage guidance is inferable but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a unique resource/action pairing—users, health summaries, timeseries, providers, and lab orders—so an agent can reliably distinguish them. Even similarly named getters are separated by the data domain (activity/body/sleep/workouts) and description.
All tools use the vital_ prefix and snake_case verb_noun forms, which is highly predictable. Minor inconsistency: get is used for both single-resource fetches and list-returning calls (get_workouts, get_user_connected_providers) while list is reserved for global collections.
21 tools is on the heavier side, but the breadth of the Vital API—users, providers, many health summary types, timeseries, and lab tests/orders—justifies most of them. It is slightly over a typical focused MCP server but not bloated or redundant.
The read side is strong: users, providers, summaries, timeseries, lab tests, and results are all covered. However, there are no update/delete user operations and no way to create a lab-test order, so core lifecycle/workflow gaps remain.