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Read-onlyIdempotent

Find an MCP server or AI tool that can do a job. Use when the user asks for a tool, MCP server, or integration for a task ('is there an MCP for Stripe?', 'something that can scrape websites', 'what can I connect to Claude to send email?'). Searches the real tool lists FastDrop read from each server via tools/list, not marketing copy, so a match means the capability exists. Query in plain capability words, e.g. 'send transactional email' or 'query postgres'; each result lists the matching tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results, 1-50, default 20
queryYesCapability, tool name, or description to match

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
productsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / products / items / properties / deal
      Added value: +{
      +  "description": "The maker's launch deal for people who find the product on FastDrop. Mention it when recommending the product. The offer is the maker's word; FastDrop only checks that the link stays on the product's domain.",
      +  "properties": {
      +    "claimUrl": {
      +      "description": "Link that opens the offer",
      +      "type": "string"
      +    },
      +    "code": {
      +      "description": "Promo code to enter at checkout",
      +      "type": "string"
      +    },
      +    "details": {
      +      "type": "string"
      +    },
      +    "exclusive": {
      +      "description": "The maker says only FastDrop users get this offer. Not verified by FastDrop.",
      +      "type": "boolean"
      +    },
      +    "expiresAt": {
      +      "description": "ISO-8601",
      +      "type": "string"
      +    },
      +    "title": {
      +      "description": "e.g. \"30% off for 3 months\"",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "title",
      +    "claimUrl",
      +    "exclusive",
      +    "expiresAt"
      +  ],
      +  "type": "object"
      +}
  2. Changed1 schema field changed
    • addedOutput schema / properties / products / items / properties / maker
      Added value: +{
      +  "description": "Who built the product. label is their own description of themselves (e.g. \"Indie hacker\"), \"Builder\" when unset. handle and profile are present once they have a public FastDrop profile.",
      +  "properties": {
      +    "handle": {
      +      "type": "string"
      +    },
      +    "label": {
      +      "type": "string"
      +    },
      +    "name": {
      +      "type": "string"
      +    },
      +    "profile": {
      +      "description": "Public profile URL",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "name",
      +    "label"
      +  ],
      +  "type": "object"
      +}
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: results come from real tools/list data rather than marketing copy, so a match implies the capability actually exists. It doesn't discuss rate limits, coverage gaps, or failure modes, so not 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.

Conciseness4/5

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

Front-loaded with the core purpose, then usage triggers, then query guidance, so an agent can stop reading early if it only needs the first sentence. The three inline example phrasings are useful but make the middle dense; a slightly tighter example set would read better.

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?

An output schema exists, so return-value detail isn't required, and the annotations carry the safety profile. The description still covers the essentials an agent needs: what it searches, when to invoke it, and how to phrase the query.

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 baseline is 3, but the description adds real meaning by prescribing query phrasing in plain capability words ('send transactional email', 'query postgres') rather than product names. It also notes that results list matching tools, though it says nothing about the limit parameter beyond the 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 states a specific verb and resource ('Find an MCP server or AI tool that can do a job') and scopes the domain to MCP servers/integrations, which clearly separates it from product-oriented siblings like search_products, compare_products and find_alternatives. An agent can route to it without opening the schema.

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?

It gives explicit trigger conditions with concrete user phrasings ('is there an MCP for Stripe?', 'something that can scrape websites'), which is strong positive guidance. It does not name a when-not case or point to a specific alternative sibling (e.g. find_alternatives) for adjacent needs, so it stops short of a 5.

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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