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maviapi

maviapi

by kuzenlabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Show a maviapi API

get_api
Read-onlyIdempotent

Show an API's endpoint details—what each returns, required parameters, and response fields—using its slug or site domain before calling it.

Instructions

Show one maviapi API's endpoints: what each returns, its parameters (required ones marked), and the fields in the response. Accepts the API slug from search_apis, or the site's domain (e.g. "airbnb.com"). Read this before call_api.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "api": "<api>"
    },
    "name": "get_api"
  }
}

Input Schema

NameRequiredDescriptionDefault
apiYesAPI slug (e.g. "booking") or the site's domain.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds real value by disclosing the shape of the informational payload (per-endpoint returns, marked-required parameters, response fields). It stops short of saying what happens with an unknown slug or domain, which would have made it a 5.

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, no filler. The output-content statement comes first and the ordering constraint ('Read this before call_api') is placed last where it functions as a routing instruction.

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 carries the burden of describing the return, and it does so at the right level of abstraction for a documentation-lookup tool. It is nearly complete; only error/not-found behavior and the response format (structured vs. markdown) are unaddressed.

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 coverage is 100%, so the baseline is 3 and the schema already names both acceptable forms. The description adds provenance semantics — that the slug comes from search_apis and that a site domain such as "airbnb.com" is acceptable — which helps the agent construct valid input rather than guess.

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 states a specific verb and resource ('Show one maviapi API's endpoints') and enumerates what is returned: endpoints, what each returns, parameters with required ones marked, and response fields. This clearly separates it from search_apis (discovery) and call_api (execution).

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

Usage Guidelines5/5

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

It names the upstream source of its input ('the API slug from search_apis') and an explicit ordering rule ('Read this before call_api'), which routes the agent through the correct workflow. The only minor omission is that no explicit when-not-to-use case is stated, but the sequencing rule effectively covers it.

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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