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ScrapeCreators MCP Server

ScrapeCreators MCP Server

by thenavidm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Transcript

facebook_transcript

Extract the transcript text from a Facebook video post or reel as a single string with line breaks. Works only on videos under 2 minutes long.

Instructions

Extracts the transcript text from a Facebook video post or reel. Returns the transcript as a single text string with line breaks. Only works on videos under 2 minutes in length. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

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": {
      "url": "<url>"
    },
    "name": "facebook_transcript"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesFacebook post URL
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

A3.8/5.0
Behavior4/5

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

Adds context the annotations cannot convey: potential paid-credit consumption, the confirm=true gate, and the explanation that read-like POSTs do not publish to social platforms, which reconciles the readOnlyHint=false annotation. It does not mention rate limits or failure behavior on private/age-gated videos.

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, front-loaded with what is returned and its shape, then the hard limit, then the cost/gate caveat. No sentence is padding.

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 specifies the return format (single text string with line breaks) and the main preconditions. It leaves the multi-account/cache selection behavior entirely to the schema, which is reasonable given 100% coverage but leaves the credit-confirmation workflow slightly implicit.

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 url, account, confirm, and cache_max_age are already documented including the caching/credit mechanics. The description restates the confirm requirement but adds no syntax or format detail beyond the structured fields, so baseline 3 applies.

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 and resource ('Extracts the transcript text from a Facebook video post or reel') plus the platform, which cleanly separates it from the many sibling *_transcript tools. It never names those siblings (tiktok_transcript, instagram_transcript, facebook_ad_library_ad_transcript), so differentiation is by platform inference rather than explicit routing.

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?

Gives concrete applicability constraints – videos must be under 2 minutes, confirm=true is required, credits may be consumed – which tells the agent when the call will fail. It stops short of stating when to prefer this over other transcript tools or what to do when the video exceeds the length limit.

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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