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thenavidm

ScrapeCreators MCP Server

by thenavidm

Posts

threads_posts

Fetch a Threads user's recent public posts with captions, engagement counts, and media to support profile research and content analysis.

Instructions

Fetches the most recent posts from a Threads user, returning id, caption text, code, like_count, reshare_count, direct_reply_count, repost_count, image_versions2, video_versions, and taken_at. Only the last 20-30 posts are publicly visible. Supports 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 Read-like POST requests do not publish to social platforms.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
handleYesThreads username
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

A3.7/5.0
Behavior4/5

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

With annotations declaring readOnlyHint=false and idempotentHint=false, the description adds real value beyond them: it warns that the call consumes paid API credits, requires confirm=true, and clarifies that this read-like POST does not publish to social platforms — directly defusing the misleading readOnlyHint=false. This is genuinely helpful behavioral disclosure.

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?

Three dense sentences, front-loaded with purpose and return fields, then constraints. The field enumeration is long but justified given there is no output schema. Little wasted verbiage.

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?

For a tool with no output schema, enumerating the return fields is the right compensating move, and it covers credit cost, the confirm gate, and the 20-30 post visibility ceiling. Only the absence of guidance about sibling alternatives keeps it short of complete.

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 trim, handle, account, and confirm are all already documented. The description's mention of trim and confirm largely restates the schema; it adds only marginal gloss (trim = lighter response) rather than new meaning. Baseline 3 is appropriate.

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?

States a specific verb (fetches), resource (most recent posts from a Threads user), and enumerates the returned fields, so the agent immediately knows what comes back. It does not explicitly distinguish itself from close siblings like threads_profile, threads_post, or threads_search_by_keyword, but the 'user's recent posts' scope is unambiguous on its own.

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?

Provides useful operational context (only the last 20-30 posts are public, trim for lighter responses, confirm=true required) but never states when to pick this tool over threads_post or threads_search_by_keyword. Usage is implied rather than directed.

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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