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find_mcp_or_api

Which MCP server or API does this? Matches from the official MCP registry (37,000+ servers) and the APIs.guru OpenAPI directory (2,500+ APIs), refreshed hourly, with how to connect, description, docs, spec and last-updated date; plus our measured status for matching Arc agents. Listed is not working: we do not test these. A search with no match is refused before payment. $0.003 per call over x402 (USDC on Arc, Base or Solana, or XNT on X1). Call once without payment for the terms, sign them with your own wallet, call again with payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYeswhat tool or API you need, in plain words
kindNoany (default), mcp or api
limitNoresults, 1-20 (default 10)
paymentNoa signed x402 payment (the base64 payload you would put in PAYMENT-SIGNATURE). Pass it and the purchase completes inside this tool call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses pricing ($0.003/call via x402 in specific tokens), the required payment-signing flow, that results are refreshed hourly, that listings are not verified as working, and that a no-match search is refused before payment. Cost, auth mechanics and refusal semantics are all surfaced.

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?

Front-loaded with the core question ("Which MCP server or API does this?") followed by sources, returns, caveats and payment. Dense and largely waste-free, though the payment sentence is long and could be tightened.

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 4-parameter, no-annotation, no-output-schema tool, the description covers purpose, sources, returned fields, cost and the payment handshake, which is enough to invoke correctly. Minor gaps remain around rate limits and result-shape details.

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; the description earns above baseline by explaining the two-call `payment` protocol (first call returns terms, second call with the signed payload completes the purchase inside the call), which adds protocol meaning beyond the schema's terse payload note.

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 — a search over MCP servers and APIs — and names both source corpora (MCP registry, APIs.guru) and the returned fields. It does not explicitly distinguish itself from lookalike siblings such as arc_catalogue_search, catalog_browse or research_search, so it falls short of the 5 bar.

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?

Gives clear usage context: query in plain words, optional kind filter, and an explicit two-step payment protocol (call without `payment` for terms, sign, call again). It does not say when NOT to use this versus the many catalogue/search siblings, so no exclusion guidance is present.

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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