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Get provider

get_provider

Retrieve metadata for a single AI provider: display name, SDK package, API base URL, docs link, and compact model list. Input a provider id or display name to get started.

Instructions

Fetch metadata for one provider: display name, AI SDK package name, API base URL, docs link, and a compact list of its models. Accepts the provider id ('anthropic') or display name ('Anthropic'). Use get_model for full per-model detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesProvider id or display name, e.g. 'anthropic' or 'OpenAI'.

Schema Changelog

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

  1. First observedv0.2.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It communicates a read-only operation through 'Fetch' and describes the return contents, but it does not disclose behavior for invalid ids, ambiguous display names, or whether the call can fail. For a simple metadata lookup this is acceptable but not richly transparent.

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?

Two sentences deliver the purpose, return contents, accepted input, and the key sibling alternative with no filler. The primary behavior is front-loaded, and the alternative routing is placed at the end without wasting words.

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?

For a single-parameter lookup tool with no output schema, the description adequately covers what the tool returns and how to route to get_model for deeper detail. It could mention what happens when the provider is not found, but overall it is complete enough for correct invocation.

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?

The schema already documents the parameter with examples, and description coverage is 100%, so the baseline is 3. The description adds an additional example ('Anthropic') and clarifies the accepted forms, but this mostly echoes the schema rather than adding substantial new meaning.

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 a specific verb and resource: 'Fetch metadata for one provider', then enumerates exactly what is returned (display name, package name, base URL, docs link, model list). It also distinguishes itself from get_model by noting that get_model provides full per-model detail, so an agent can tell them apart.

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?

The description clearly says to use get_model when full per-model detail is needed, providing an explicit alternative and condition. It does not explicitly mention list_providers for enumerating all providers, but the singular framing and sibling name make the distinction inferable.

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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