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DesMartin01

InferenceIndexer MCP Server

get_provider

Get detailed information about a specific AI inference provider, including its models, tier breakdown, and price range. Use it to evaluate provider offerings and pricing for informed decisions.

Instructions

Get detail for one provider: models, tier breakdown, price range.

Args: provider_name: Provider name, e.g. 'DeepInfra', 'Novita', 'Venice'. Returns: provider detail with model list and pricing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
provider_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return behavior (provider detail with model list and pricing) and the scope of the operation. There are no side effects to mention for a 'get' operation, and the return content is adequately described.

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 compact, front-loaded with the purpose, and uses a clear Args/Returns structure. Every sentence adds value with no redundancy or 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 one-parameter, read-only tool with an output schema, the description is complete. It specifies the input format with examples and the high-level return content. The output schema can handle detailed structure, so the description need not elaborate further.

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?

The input schema provides only the parameter name and type, with 0% coverage. The description compensates by explaining that provider_name is the provider name and giving concrete examples ('DeepInfra', 'Novita', 'Venice'), making the expected value unambiguous.

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 action ('Get detail for one provider') and the specific resource ('provider'), and enumerates what detail is included (models, tier breakdown, price range). It distinguishes from siblings like list_providers by explicitly scoping to a single provider.

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?

Usage is implied by the description: use when you need detailed information about a specific provider. However, it does not explicitly mention alternatives or when not to use this tool, leaving the decision to the agent's inference from the sibling tool names.

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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