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Call an API endpoint

call_api

Make a live request to a dataandapis.com API with the user's API key (sent as X-Api-Key on this MCP connection). Give the API slug, the endpoint path from get_api (path parameters already filled in, e.g. '/v1/products/3017620422003'), optional query parameters and, for POST, a JSON body. Most calls cost 1 token.

Input Schema

NameRequiredDescriptionDefault
bodyNoJSON body for POST endpoints.
pathYesEndpoint path such as '/v1/screen'. A leading '/v1' is added when missing.
slugYes
queryNoQuery parameters.
methodNoGET

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It does disclose the important traits: authentication via the user's API key sent as X-Api-Key, that the request is live (real network call with real effects), and that calls are metered at roughly 1 token. It does not disclose what happens on failure, whether POST calls have irreversible effects, rate limits, or the shape of the response.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the verb, target service, and auth mechanism, then the required inputs, then the cost note. Dense but every clause carries information. The example path in the middle of sentence two makes it slightly harder to scan than a pure bullet structure, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations, so the description is the only source of behavioral information — and it omits the return format, error representation, and how token cost is reported. For a generic API passthrough with a nested 'query' object and a POST body, an agent can construct the call but cannot anticipate the response.

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?

At 60% schema coverage the description usefully compensates: it explains that 'slug' identifies the API, that 'path' must be the endpoint path from get_api with path parameters already substituted, and gives a concrete example. It also clarifies query is optional and body applies to POST. It never mentions the 'method' parameter directly, relying on 'for POST' to imply it, which leaves the enum/default undocumented in prose.

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?

States a specific verb and resource: 'Make a live request to a dataandapis.com API.' It also distinguishes itself from siblings by naming get_api as the source of the endpoint path, implying search_apis/get_api are discovery tools and this is the execution tool. It stops short of an explicit 'unlike get_api, this actually calls the API' contrast.

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 workflow is implied rather than stated: the path comes 'from get_api' and the example shows path parameters already filled in. It also notes 'Most calls cost 1 token,' which is a useful usage consideration. But there is no explicit when-not-to-use guidance, no statement that get_api must be called first, and no guidance on error or retry behavior.

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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