List providers
list_providersList all tracked AI model providers (OpenAI, Anthropic, Google, etc.) with a short description and their pricing page.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
mcp
TDQS
A4.4/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses that the tool lists providers with descriptions and pricing pages, indicating a read-only nature with no destructive behavior.
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 a single well-structured sentence that conveys all necessary information without redundancy.
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?
Given no output schema, the description adequately explains the return values (short description and pricing page), making it complete for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the description adds value by specifying the output includes short descriptions and pricing pages, fully compensating for the lack of a parameter schema.
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 clearly states the tool lists all tracked AI model providers with short descriptions and pricing pages, distinguishing it from sibling tools that focus on models and pricing.
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?
The description does not explicitly state when to use this tool versus alternatives, but the context of sibling tools implies it is for provider overviews while others are for model-specific tasks.
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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TDQS
A4.3/5.0
Disambiguation5/5
Each tool targets a distinct operation: searching, retrieving full details, comparing, finding cheapest, and listing providers. The descriptions clearly delineate what each tool does, and there is no ambiguity about when to use one over the other.
Naming Consistency4/5
Most tool names follow a verb_noun pattern (search_models, get_model_pricing, compare_models, list_providers). The exception is 'cheapest_models', which uses an adjective instead of a verb, creating a minor inconsistency but still readable and clear.
Tool Count5/5
Five tools is a well-scoped set for a model pricing server. Each tool covers a distinct aspect of the domain—search, detail, comparison, ranking, and provider listing—without unnecessary bloat or gaps.
Completeness5/5
The surface covers the core read-only operations for the domain: finding models, getting detailed pricing, comparing models, and browsing providers. There are no obvious dead ends, and the search functionality can filter by provider or name, covering most use cases.