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aimarket-mcp

aimarket-mcp

by alexar76
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

web_search_tool

Search the web for current facts and return top result snippets. Use this to answer questions dependent on recent events or documentation.

Instructions

Search the web for current facts and return the top result snippets.

Uses DuckDuckGo HTML results. Output is sanitized and wrapped <untrusted> like web_fetch. Prefer this over guessing when the answer depends on recent events or documentation.

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": {
      "query": "<query>"
    },
    "name": "web_search_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesNatural-language search query for live web facts. Example: 'PyPI aimarket-metis release date'

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Discloses backend (DuckDuckGo HTML) and output sanitization/wrapping (<untrusted>). No annotations provided, so description carries burden; it gives useful context but omits potential rate limits or result count limits.

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?

Three sentences, no wasted words. Front-loaded with purpose. Every sentence adds value.

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?

Tool is simple with one param. Description covers backend, output format, and usage context. Output schema exists but description doesn't detail full return structure; however, 'top result snippets' and wrapping info suffice.

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?

Single parameter 'query' has schema description (100% coverage). Description adds an example and context ('natural-language', 'live web facts'), enhancing meaning 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?

Description clearly states verb ('search'), resource ('web'), and output ('top result snippets'). Differentiates from siblings by recommending use over guessing for recent events.

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?

Explicitly states when to prefer this tool ('when the answer depends on recent events or documentation'). Lacks explicit exclusions or when not to use, but the positive guidance is clear.

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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