vital_get_mealGet meal summaries for a user over a date range. Vital API: GET /v2/summary/meal/{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?
The readOnlyHint annotation already marks this as a safe read operation, and the description aligns by saying 'Get' and referencing the GET endpoint. It adds context that this is meal summary data for a date range, but does not disclose pagination behavior, response shape, or any API-specific quirks.
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?
Two short, focused sentences. The first states the action and scope, and the second provides the exact API endpoint. There is no filler or redundancy.
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 summary endpoint, the description plus fully covered schema provides enough to call the tool correctly. It names the resource, scope, user, and date range. It could be more complete by describing return values or pagination since there is no output schema, but the lack is not blocking for a straightforward GET.
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 the parameters are already fully documented with types, patterns, and required status. The description only restates 'user' and 'date range' and does not add meaningful parameter semantics beyond the schema.
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 states a specific verb and resource: 'Get meal summaries for a user over a date range.' The 'meal' resource clearly distinguishes this tool from sibling vital_get_* tools such as vital_get_activity or vital_get_sleep, so an agent can tell what it does at a glance.
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 description implies usage context: call this when meal summaries are needed for a user over a date range. However, it does not explicitly state when to prefer this over alternatives or mention exclusions such as unsupported providers or time constraints beyond the date range.
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.