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306,895 tools. Last updated 2026-07-27 07:28

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  • Youtube

    YouTube MCP — wraps the YouTube Data API v3 (BYO API key)

  • youtube-transcripts

    YouTube transcripts, subtitles, and video metadata as structured JSON via an Apify Actor.

  • polymarket_arbitrage

    Youtube

    Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • get_channel_transcripts

    YouTube Transcript Downloader

    Get transcripts for a YouTube channel's most recent videos (newest first) as timestamped markdown, one section per video. Use for research across a creator's recent output; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
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  • list_new_channel_videos

    YouTube Video Summarizer (pay-per-call)

    New videos on a YouTube channel since your last poll — stateless channel monitoring, no accounts or webhooks. Pass a channel URL, @handle, or channel id, plus an optional cursor (`since_video_id` or `since`, an ISO 8601 timezone-aware timestamp) from your last call. Returns new video ids/titles/publish times, newest first, plus `newest_video_id` to use as your next cursor. Pay-per-call via x402 (USDC on Base), no account or API key. An unresolvable channel or a naive `since` timestamp returns an error and is not charged.
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  • get_playlist_transcripts

    YouTube Transcript Downloader

    Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
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  • polish_transcript

    YouTube Transcript Downloader

    Get a cleaned-up transcript of a YouTube video's auto-generated captions: punctuation and capitalisation restored, filler and false starts removed, paragraphs added, misheard names fixed, faithful to what was said. Use when raw captions are too messy to read or quote; for a plain transcript use get_transcript. Read-only; requires an API key. Each call charges credits by transcript length (about 3 per 1,000 words, minimum 5), including repeat calls, so keep the result in context. Human-uploaded captions (already clean) and transcripts over ~7,000 words return an error without charging. Rate limit: 5 requests per 10 seconds.
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  • get_playlist_transcripts

    YouTube Transcript Downloader

    Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
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  • post_to_youtube

    Hermoso

    Publish a finished video to the brand’s connected YouTube channel. Pass a Hermoso render URL (or an upload_file url for a local/external file). DEFAULTS TO UNLISTED (link-only — not on the channel, not searchable, but shareable by link AND usable as a YouTube/Google ad). Pass privacy:"public" to put it ON the channel (a public publish — confirm with the user first) or privacy:"private" for eyes-only. Do NOT use "private" for anything meant to run as an ad — private videos CANNOT be used as ads; unlisted is the ad-ready setting. Needs a connected YouTube channel (Settings ▸ Connectors ▸ YouTube).
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  • deep_research

    Youtube

    ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1354 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,141 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
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  • polish_transcript

    YouTube Transcript Downloader

    Get a cleaned-up transcript of a YouTube video's auto-generated captions: punctuation and capitalisation restored, filler and false starts removed, paragraphs added, misheard names fixed, faithful to what was said. Use when raw captions are too messy to read or quote; for a plain transcript use get_transcript. Read-only; requires an API key. Each call charges credits by transcript length (about 3 per 1,000 words, minimum 5), including repeat calls, so keep the result in context. Human-uploaded captions (already clean) and transcripts over ~7,000 words return an error without charging. Rate limit: 5 requests per 10 seconds.
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  • create_style

    framesail

    Create a style. Two mutually exclusive paths: References (best): inputs=[{"input_type": "youtube" | "text", "value": "<url or description>"}] — YouTube videos are watched and text directions read; async analysis writes the style's art/narrative/director fields: await_jobs(style_id=...) before using the style. (Image/video FILE references require the multipart REST endpoint POST /styles.) Presets (instant, no analysis): presets={"art_style": id, "narrative_style": id, "director_style": id} — all three axes, ids from list_style_presets.
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  • report_outcome

    VHGENGINE

    Report what a bought hook actually did once posted. FREE (WP-H). Honest telemetry feeding the outcome corpus (no view prediction claimed). Args: hook_id, platform (tiktok|instagram|youtube|x|other), posted_at (ISO, not >48h future), views/likes (0..1e11), retention_pct? (0-100), url? (http(s)+host), api_key, idempotency_key. Caps 20/hook, 500/day; an exact duplicate is a conflict. Returns {outcome, aggregate, reward_credits, credits_remaining?}. Errors: unauthorized, not_found, invalid_request, conflict, rate_limited.
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  • analyze_video_report

    switch

    Run the FULL Switch Vision analysis on a video, the same premium report the Video Analysis page produces: it watches AND listens in three forensic passes and returns a structured report with every category: overview (scores and takeaways), a second by second timeline, audio, visual craft, story and retention, speech transcript, ready to run recreation prompts, and metadata. Pass video_url (a public https video URL, YouTube included) OR one of your own Switch video ids. For an external file also pass duration_seconds (YouTube and your own videos are measured automatically) because the analysis is billed per second. Optional question focuses the analysis. Returns a report_id right away; poll get_vision_report until status is succeeded (a few minutes). If it cannot finish, your tokens are returned automatically. For one quick question about a video use analyze_video instead; this tool is the full paid report.
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