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subimpact-data-mcp

Official
by subimpact
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TypeScript
Remote

youtube

Collect videos, Shorts, channels, playlists, and comments from search queries or URLs without an API key, with optional detail enrichment and comment replies.

Instructions

YouTube Scraper: Videos, Shorts, Channels & Comments

Fast YouTube scraper with no browser and no API key: keyword search with filters, channel videos and Shorts, channel About data, playlists, video details (exact likes, date, description) and comments with replies. $1.00 per 1,000 results.

Pricing (pay per event, billed to your Apify account): Result: $0.001; platform usage billed to your account.

Runs on Apify as subimpact/youtube-scraper.

Input Schema

NameRequiredDescriptionDefault
countryNoTwo-letter country code (gl), e.g. 'US'.US
languageNoInterface language code (hl), e.g. 'en'.en
_maxItemsNoHow many dataset items to return to the model (1-1000, default 50). Truncates the response only; it does not change what the Actor collects or charges for.
startUrlsNoYouTube URLs: videos (/watch?v=, youtu.be), Shorts (/shorts/), channels (@handle, /channel/, /c/, /user/) or playlists (?list=).
searchSortByNoSort order for search results.relevance
_maxChargeUsdNoPer-run spending cap in USD (default 0.5). Passed to Apify as the run option maxTotalChargeUsd, so the run stops when it reaches this charge.
searchQueriesNoKeyword searches to run. Each query yields up to 'maxResultsPerQuery' results.
channelContentNoWhich tab to scrape for channel URLs ('videos', 'shorts' or 'both'). A /@handle/shorts URL always forces Shorts.videos
commentsSortByNoComment order: 'top' (most upvoted) or 'newest'.top
includeRepliesNoAlso scrape replies to comments.
maxConcurrencyNoHow many inputs are processed in parallel. Pagination inside one input is sequential.
scrapeCommentsNoAlso scrape comments for each video (adds 'comment' rows to the dataset).
maxTotalResultsNoGlobal cap on total rows across all inputs. Hard stop: no rows past this number.
searchUploadDateNoUpload-date filter for search results.any
enrichVideoDetailsNoFetch the video page for every result for exact like counts, exact publish date, full description and comment count. One extra request per video.
includeChannelInfoNoFor every channel URL, also deliver one 'channel' row with subscriber counts, About-panel info and links.
maxResultsPerQueryNoMaximum rows per search query.
proxyConfigurationNoOptional. Proxies are usually not needed: the scrape works over plain HTTPS from datacenter IPs. Enable Apify Proxy only for high volumes.
maxCommentsPerVideoNoMaximum TOP-LEVEL comment rows per video. Replies are capped separately by Max Replies Per Comment and do not count toward this limit.
maxVideosPerChannelNoMaximum video/short rows per channel or playlist URL.
searchIncludeShortsNoAlso extract Shorts rows from search result shelves.
maxRepliesPerCommentNoMaximum reply rows per comment thread. Reply rows do not count toward Max Comments Per Video.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the cost model ($1.00 per 1,000 results, per-event billing to the Apify account) and the no-browser/no-API-key execution profile — genuinely useful behavioral context. It does not describe the dataset/row output shape, run latency, or failure modes, leaving meaningful gaps for a 22-parameter scraping run.

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?

Capability statement comes first and is dense and useful. Minor waste: pricing is stated twice ('$1.00 per 1,000 results' and 'Result: $0.001'), and 'Fast … no browser and no API key' is marketing framing rather than decision-relevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 22-parameter, nested-object, no-output-schema tool, the description covers input modes and cost but says nothing about the returned dataset structure beyond scattered mentions of 'comment' and 'channel' rows, and nothing about the Apify account/token prerequisite. Adequate to start a run, not complete enough to predict results.

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

Parameters4/5

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

Schema description coverage is 100% with per-parameter descriptions, defaults and enums, so the baseline is a 3. The description lifts it slightly by naming the output modes the parameters switch between — exact likes/date/description via enrichment, comments with replies, channel About rows — giving the agent a reason to flip those flags rather than just their syntax.

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 concrete resource set (videos, Shorts, channels, comments, playlists, channel About data) and the supported access modes (keyword search with filters, channel URLs, playlist URLs). The platform name alone separates it from siblings such as tiktok_hashtag or pinterest, so an agent can route to it 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?

Usage is only implied: the description lists the capabilities (search, channel, playlist, comments), from which an agent must infer that it should supply searchQueries or startUrls. There is no explicit statement of when to prefer this over google_search or web_page_markdown, and no exclusions or prerequisites beyond 'runs on Apify'.

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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