ScrapeMole Wiki

ScrapeMole Wiki: Wikipedia summaries, Wikipedia search and Wikidata facts for AI agents (attributed): Wikipedia search

search

Read-onlyIdempotent

Use to find the right Wikipedia article before reading it: full-text search over one Wikipedia language edition, returning up to 20 results with title, plain-text snippet, page URL, word count and last edit time, ranked by relevance. Results are titles and snippets only; use /v1/summary for content. Paid tool: x402 USDC on Base, $0.001 per successful call; call without payment to receive the PaymentRequired object.

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": {
      "q": "<q>"
    },
    "name": "search"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Search text.
`lang`	No	Wikipedia language code.	en
`limit`	No	Max results (1-20).	10

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 11, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations only cover safety (readOnly/openWorld/idempotent); the description adds substantial non-annotation behavior: the x402 USDC-on-Base payment model, $0.001 per successful call, and that calling without payment returns a PaymentRequired object. It also discloses the exact result fields and relevance ranking.

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 dense but purposeful sentences, front-loaded with the use case and then the return shape and payment model. No filler and nothing repeated from structured fields.

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?

With no output schema, the description compensates by enumerating the returned fields (title, snippet, URL, word count, last edit time). Payment/error behavior is also covered, so an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so q, lang, and limit are already documented. The description only reinforces the limit ceiling ('up to 20 results') and ranking behavior, adding marginal value over the schema baseline.

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?

States a specific verb+resource (full-text search over one Wikipedia language edition) and its scope (returns titles/snippets, ranked by relevance). It also distinguishes itself from siblings by naming /v1/summary as the content-reading alternative.

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?

Explicitly says when to use it ('find the right Wikipedia article before reading it') and when not to rely on it for content ('use /v1/summary for content'). The sibling routing is unambiguous.

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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