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ScrapeCreators MCP Server

by thenavidm

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pinterest_search

Search Pinterest for pins matching a query, returning detailed results with images, links, and board info. Supports pagination and trimmed responses for lighter data.

Instructions

Searches Pinterest for pins matching a query, returning results with id, url, title, description, images, link, domain, board info, and pinner details. Supports pagination via cursor and a trim option for lighter responses. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trimNoSet to true for a trimmed down version of the response
queryYesSearch query
cursorNoCursor
accountNoNamed private ScrapeCreators account; selects credentials, not a remote account ID.
confirmNoMust be true for the specific approved credit-consuming research call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Adds real context beyond the annotations: it warns that calls may consume paid API credits, requires confirm=true, and pre-empts concern by noting the read-like POST does not publish to social platforms. This meaningfully clarifies the readOnlyHint=false annotation, though it omits rate-limit or partial-failure behavior.

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?

Two sentences, front-loaded with the core action; the return-field list is somewhat long but legitimately informative since there is no output schema. Every sentence carries weight, though the field enumeration could be trimmed.

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?

With no output schema, the description usefully covers return fields, and it addresses pagination and the confirm/credit requirement. Given a five-parameter read tool, this is nearly complete; only edge behaviors and error handling are absent.

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 description coverage is 100%, so the schema already documents query, cursor, trim, account, and confirm. The description only echoes cursor pagination and the trim option, adding no syntax or format detail beyond the structured fields, which lands on the 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 and resource ('Searches Pinterest for pins matching a query') and enumerates the returned payload fields, making the scope unambiguous next to siblings like pinterest_pin, pinterest_board, and pinterest_user_boards. An agent can distinguish this wide search from the narrower pin/board lookups 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 Guidelines3/5

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

The description implies usage ('matching a query', pagination via cursor, trim for lighter responses) but never names an alternative or states when to prefer pinterest_search over pinterest_pin or a board-level tool. Conditions like confirm=true are stated, but the core use-vs-alternative routing is left to inference.

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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