Skip to main content
Glama

apis-io

by io.apis
OverviewDiscussionsAdmin

get_tag

Read-only

One tag: its metadata, neighbor tags, and a top sample of its providers and APIs (with totals). provider_count counts companies that classify THEMSELVES here; api_provider_count counts the ones reached only through an API or operation tag — the two are disjoint, and a tag with no providers and many APIs names a resource, not a market. age summarises when the members were created (created_last_30d/90d, the largest same-day batch, and how much of the first page by composite is under 30 days old) — a high first_page share means the top of the tag is new listings, and find_providers(tags, sort:"created") lists them newest first. Use find_apis?tags=slug / find_providers?tags=slug for the full ranked list, or view=full here. Results carry next: the sub-resources that exist for this entity and the exact tool call that retrieves each, computed from this record. Pass include_next=false to omit it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
viewNosummary (default) returns lean discovery records + *_count for dropped sections; full returns the whole record (use get_api / get_provider for one entity).summary
limitNoTop members to show per list.
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
include_nextNoSet false to omit the `next` affordance block.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Optional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / include_next
      Added value: +{
+  "default": true,
+  "description": "Set false to omit the `next` affordance block.",
+  "type": "boolean"
+}
  3. Changed2 schema fields changed
    • addedInput schema / properties / limit
      Added value: +{
+  "default": 25,
+  "description": "Top members to show per list.",
+  "maximum": 100,
+  "minimum": 1,
+  "type": "integer"
+}
    • addedInput schema / properties / view
      Added value: +{
+  "default": "summary",
+  "description": "summary (default) returns lean discovery records + *_count for dropped sections; full returns the whole record (use get_api / get_provider for one entity).",
+  "enum": [
+    "summary",
+    "full"
+  ],
+  "type": "string"
+}
  4. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description adds non-obvious behavior: provider_count versus api_provider_count are 'disjoint', their different meanings are explained, and the age field is interpreted so the agent understands what high first_page share implies. It also discloses the computed `next` affordance and how to suppress it.

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 dense but every clause earns its place: it front-loads the core purpose, then explains count semantics, age interpretation, alternative full-list tools, and the next affordance. Despite its length, there is no filler or repeated schema content.

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?

With no output schema, the description carries the full burden of explaining results, and it does so well: it covers returned sections, count semantics, age meaning, navigation to full lists, and the next affordance. An agent has enough context to decide when to call this tool and how to interpret the response.

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 80%, with view, limit, context, and include_next already described in the schema. The description reinforces view=full and include_next=false but does not add much that is not already in the schema; the required slug parameter is still left to inference, though its meaning is fairly self-evident.

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 opens with 'One tag: its metadata, neighbor tags, and a top sample of its providers and APIs (with totals)', which names a specific resource and the exact pieces of data returned. This clearly distinguishes get_tag from list-oriented siblings like find_tags and find_providers by focusing on the single-entity view.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly routes to alternatives: 'Use find_apis?tags=slug / find_providers?tags=slug for the full ranked list, or view=full here.' It even points to find_providers with sort:"created" when the user wants newest-first listings, giving concrete conditions for choosing another tool.

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

All apis-io toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources