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API Hub MCP — 337+ Tools

API Hub MCP — 337+ Tools

by scotia1973-bot
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

unique_words

Count unique words and their frequencies in any text to understand vocabulary usage.

Instructions

Count and list unique words with their frequencies.

Parameters:
    text — Text to extract unique words from.

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": {
      "text": "<text>"
    },
    "name": "unique_words"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.4.1

TDQS

B3.1/5.0
Behavior2/5

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 only states the action (count and list frequencies) without disclosing behavioral traits like case sensitivity, punctuation handling, or output format. Behavioral details are minimal.

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?

The description is brief with two sentences plus a parameter line. It is front-loaded and efficient, though the parameter list is somewhat redundant with the schema. No wasted words.

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?

For a simple one-parameter tool with an output schema, the description is adequate but incomplete. It does not address edge cases (empty text), define 'unique words' (case sensitivity, punctuation), or specify the return format, relying on the output schema for 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?

The input schema has 0% description coverage (no property descriptions), so the description adds meaning by explaining the 'text' parameter as 'Text to extract unique words from'. This provides context beyond the schema's type definition.

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?

The description clearly states the tool counts and lists unique words with frequencies, using a specific verb and resource. It distinguishes itself from similar tools like 'word_frequency' or 'repeated_words' by focusing on unique words, though it could be more explicit about the contrast.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus siblings. The description does not mention when not to use it or suggest alternatives, leaving the agent without context for selection.

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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