can-i-use

Get Feature By Id

get_feature_by_id

Read-onlyIdempotent

Support table for an exact caniuse feature id.

Use when the id is already known, for example from a previous search. No fuzzy matching is applied.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Exact caniuse feature id, e.g. "css-has".

Output Schema

TableJSON Schema

Name	Required	Description
`spec`	No
`title`	Yes
`feature`	Yes	Resolved caniuse feature id.
`meaning`	Yes	One sentence, safe to show a user verbatim.
`support`	Yes	Per-browser detail, keyed by caniuse browser id.
`description`	No
`safe_to_use`	No	True only when global support is at least 90% AND no major browser is missing it. A conservative single answer.
`other_matches`	No	Other features the query could have meant.
`resolved_from`	No	The query that was matched, so a caller can see what it actually asked about.
`unsupported_in`	No	Major browsers whose newest release still does not support it.
`global_partial_percent`	No
`global_support_percent`	No	Percentage of tracked global users on a browser version that fully supports it.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, non-destructive), lowering the burden. The description adds genuine behavioral context beyond the schema and annotations: exact-match-only semantics, no fuzzy matching, and that the tool serves as a 'support table' lookup.

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?

Three short sentences, each earning its place: core purpose, usage condition, and exclusionary behavior. The most decision-relevant information is front-loaded, and there is zero filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter lookup tool with a rich annotation set and an output schema, nothing essential is missing. The description covers what the tool does, when to use it, and how it differs from the sibling search tool; the output schema eliminates the need for return-value documentation.

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 description coverage is 100%, and the schema already documents the single 'id' parameter with a concrete example ('css-has'). The description reinforces that the id must be exact and known in advance but adds no formatting or syntax detail beyond what the schema provides, so the baseline of 3 applies.

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 states a specific resource (caniuse feature) and the lookup-by-id operation, and explicitly distinguishes itself from siblings by declaring 'No fuzzy matching is applied.' It is immediately clear this is the exact-ID retrieval tool versus a general search.

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?

'Use when the id is already known, for example from a previous search' gives a clear, actionable condition for when to invoke this tool. The 'No fuzzy matching' statement implies the alternative (search_features) for fuzzy lookup, though it never names the sibling explicitly or states a formal when-not-to-use.

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

All can-i-use tools Inspect

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TDQS

A4.5/5.0

Disambiguation4/5

The tools have overlapping resolution ability, since check_feature_support also performs fuzzy matching, but the descriptions clearly direct when to use each: one-call lookup, exact-id lookup, and candidate search. This makes misselection unlikely in practice.

Naming Consistency5/5

All tool names follow a consistent snake_case verb-first pattern: check, get, and search. Each name clearly communicates the action and target, making the set predictable.

Tool Count5/5

Three tools is well-scoped for a focused browser-support lookup server. Each tool earns its place by covering a distinct mode: direct answer, exact ID lookup, and candidate selection.

Completeness5/5

The surface covers the complete workflow from a loose query to a support decision, including disambiguation and exact retrieval. There are no obvious dead ends for the stated purpose.

Resources

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