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ScrapeCreators MCP Server

by thenavidm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Tweet Details

twitter_tweet_details

Fetch detailed data for a specific tweet by URL, including author profile, engagement metrics, and media; supports trimmed responses.

Instructions

Retrieves detailed information about a specific tweet by URL, including the author's profile and engagement metrics. Returns rest_id, full_text, views count, favorite_count, retweet_count, reply_count, bookmark_count, quote_count, created_at, source, and media entities. Supports a trim parameter for a lighter response. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesTweet URL
trimNoSet to true for a trimmed down version of the response
accountNoNamed private ScrapeCreators account; selects credentials, not a remote account ID.
confirmNoMust be true for the specific approved credit-consuming research call.
cache_max_ageNoIf we have a response in the cache that is this many days old or newer, return the cached response (0 credits, with "cached": true and a "cached_at" timestamp). Otherwise, scrape a live result (1 credit). [See the Caching page for details.](https://docs.scrapecreators.com/caching)

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?

Annotations declare readOnlyHint=false and idempotentHint=false, so the description earns credit by explaining that the read-like POST does not publish to social platforms and that the call consumes paid credits and requires confirm=true. It stops short of describing rate limits or what a failed credit charge does, keeping it below 5.

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 front-loaded sentences with no filler; the field enumeration is slightly long but directly useful to an agent since no output schema exists.

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 and a 5-parameter credit-consuming tool, the description usefully names the return fields and the confirm/credit requirement. It omits cache behavior and account selection, which are covered in the schema, so it is largely 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 the baseline is 3; the description only restates the trim parameter's lighter-response behavior already documented in the schema and adds nothing about account or cache_max_age semantics.

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 ('Retrieves detailed information about a specific tweet by URL') and enumerates the returned fields, making it easy to distinguish from siblings like twitter_transcript or twitter_user_tweets.

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?

It surfaces prerequisites (requires confirm=true, consumes paid credits) but never states when to choose this over alternatives such as twitter_transcript or twitter_profile, nor when a plain tweet fetch is inappropriate; usage is only implied.

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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