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get_provider

Read-only

Full detail for one provider: profile, rating, and the APIs it publishes. The heavy collections and common sections are omitted by default (their counts are still reported) — pass view=full for the whole document, or fields=["common"] for a section. Narrow for cheap reads: fields=["score"] returns just the rating. Relative artifact URLs are resolved to absolute, fetchable ones. 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
fieldsNoReturn exactly these top-level keys (slug and name always included); overrides view.
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
    • changedInput schema / properties / fields / description
      Previous value: -"Top-level keys to return; slug and name are always included. Omit for the default set (everything except collections and common). Use [\"all\"] for the complete document."New value: +"Return exactly these top-level keys (slug and name always included); overrides view."
    • 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. Changed1 schema field changed
    • addedInput schema / properties / fields
      Added value: +{
+  "description": "Top-level keys to return; slug and name are always included. Omit for the default set (everything except collections and common). Use [\"all\"] for the complete document.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  5. First observed

TDQS

A4.1/5.0
Behavior5/5

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

The description adds substantial behavior beyond the readOnlyHint: heavy sections are omitted by default with counts, absolute URL resolution, and the computed next block with exact tool calls. It also tells how to disable that block. These details are not available in annotations and materially shape the result.

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?

Every sentence carries distinct value: scope, default omissions, field narrowing, URL behavior, and the next affordance. Information is front-loaded with the main purpose before options.

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?

With no output schema, the description compensates well by explaining default return shape, counts, field selection, URL resolution, and pagination-style next data. It is complete enough for most calls, though it does not enumerate every possible top-level field or error behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 80%, so the schema already documents most parameters. The description adds concrete usage meaning: fields=['score'] for rating only, fields=['common'] for a section, and view=full for the whole document, while the required slug is implicitly the provider identifier.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns full detail for one provider, including profile, rating, and published APIs, which distinguishes it from list/search tools. It does not explicitly name a sibling alternative like get_provider_apis, so the differentiation is implicit rather than stated.

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

Usage Guidelines3/5

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

It gives clear within-tool guidance: view and fields configure the response, and include_next removes the next block. However, it does not state when to prefer this tool over siblings such as find_providers or get_provider_apis, leaving alternative selection to inference.

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

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