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168,498 tools. Last updated 2026-06-03 05:07

"youtube" matching MCP tools:

  • extract_vertical_clip

    Weftly

    Cut a 9:16 vertical clip from any prior video job (find_clips, summarize, or video transcribe), suitable for direct upload to TikTok, Instagram Reels, or YouTube Shorts. Default output is 1080×1920 H.264 / AAC `.mp4` with center-cropped framing; audio loudness-normalized to -14 LUFS / -1.5 dBTP for short-form social. Single-segment only; clip duration must be between 1 and 90 seconds (Instagram Reels max). Operates on a parent job — possessing the parent `source_job_id` is the capability, no upload step. Two-call flow: (1) call with `source_job_id` + `start` + `end` (in source seconds) to receive {job_id, payment_challenge}; (2) pay via MPP and call with `job_id` + `payment_credential` to start processing. Poll get_job_status(job_id) for completion; output is role `clip-vertical-video` (the `.mp4`). Flat price: $0.50 per clip. Payment: MPP — accepts Tempo USDC and Stripe SPT. Optional `profile` parameter selects the encoding profile (default `tiktok-primary`). Allowed values: `tiktok-primary` (1080×1920, fast preset, CRF 22), `tiktok-primary-720p` (720×1280, CBR 3 Mbps — half-resolution mobile-optimized, ~40% faster wall time), `instagram-reels` (1080×1920, slow preset, CBR 4 Mbps), `instagram-stories` (same encode shape as instagram-reels). All four profiles loudness-normalize identically. Optional `subject` parameter controls reframing (default `center`, preserves today's behavior): `auto` locks onto the longest-tracked face from the parent's subjects-sidecar (or runs inline detection if the parent has none); `subject_id` (with `subject_id` param naming a face_N from the sidecar) locks onto a specific subject; `follow` switches crop between active speakers across the clip using the sidecar's active_speaker_timeline; `manual` accepts caller-supplied framing via `subject_box: {x, y, w, h}` (source pixels) or `subject_x_offset` (direct crop x). Sidecar shape at /.well-known/weftly-subjects-v1.schema.json. auto/subject_id/follow fall back to center if detection or sidecar resolution fails — the paid job always delivers a clip. Source must be a horizontal video (wider than 9:16) — already-vertical or square sources are rejected. Source must still be in storage (72h TTL for find_clips parents, 24h elsewhere — check `expires_at` from get_job_status on the parent). Pair with `find_clips` ($2.00/video) to pick a moment first, then call this to get a download-ready vertical mp4 in under 5 minutes. Multiple extract_vertical_clip calls against one parent are independent paid jobs. Failed jobs auto-refund.
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  • trend_pulse

    hooklayer

    Surface what is actually peaking in short-form video right now for a niche. Returns 3 rising opportunities (format/hook/style/topic) with QUALITATIVE growth labels (e.g. "Rising", "Early signal", "Accelerating"), per-entry signal_strength (0-1, the QUANTITATIVE anchor), sources[] (Google Trends + YouTube velocity + Reddit hot + internal corpus), signal_window, plus 2 saturated patterns to avoid AND top-level provenance with cache_age_hours and cache_status. USE WHEN the user asks "what should I post about", "what's trending in [niche]", or before generating content for the first time. Pairs after analyze_account to validate a creator's formula against current trends. Costs 1 credit. 12-hour cache per niche. TOOL HEALTH: Every response includes a `quality: { level: "full" | "partial" | "degraded", reason?: string }` field. If quality.level is "partial" or "degraded", you MUST flag this to the user explicitly in chat ("Heads up — this call returned partial data: <reason>") before reporting any results. Never silently route around a degraded response. REPORTING: When you summarize this in chat, you MUST cite the data_sources array verbatim and surface cache_status (fresh|stale) — the user needs to know if they're looking at live data. For each rising/saturated entry, cite the growth label and the signal_strength numeric anchor verbatim — DO NOT FABRICATE NUMERIC GROWTH PERCENTAGES. The upstream pipeline deliberately does not compute "+178.4%"-style growth rates (no ground-truth dataset supports it); if you see a numeric percentage in the response it came from upstream LLM hallucination, not the tool. Cite the qualitative label as written.
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  • Youtube

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

  • kirbah-mcp-youtube

    Provide token-optimized, structured YouTube data to enhance your LLM applications. Access efficien…

  • youfiliate_disconnect_youtube

    Youfiliate Smart Links

    Disconnect your YouTube account from Youfiliate. IMPORTANT: Always confirm with the user before executing this action. The `confirm` parameter must be set to true. This removes stored OAuth tokens. You will need to reconnect to use the auto-migration feature. Does NOT modify any YouTube data or video descriptions. Common errors: - Not connected: no YouTube account to disconnect. - confirm=False: you must set confirm=True after getting user confirmation.
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  • polymarket_arbitrage

    Youtube

    Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. TWO MODES: (1) `event` — pass a single Polymarket event slug; 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). (2) `topic` — pass a seed question ("Strait of Hormuz traffic returns to normal"); 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}.
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  • update_doc

    Dock

    Replace a workspace's doc body. Takes EITHER TipTap JSON (`content`) OR Markdown (`markdown`): pass markdown when you're producing prose from scratch (CommonMark + GFM is the format every LLM emits natively), pass TipTap JSON when you need structural edits to an existing doc (round-trip from get_doc, mutate, write back). Beyond CommonMark + GFM, the markdown layer recognizes: - **![alt text](https://…)** → inline image. Use ANY publicly-reachable URL (HTTPS preferred — HTTP fires browser mixed-content warnings; data: URIs are rejected by `allowBase64: false`). Renders block-feeling via CSS (max-width 100%, rounded corners, drop shadow) even though the underlying node is inline. The `alt` text is the accessible label and shows in place of the image if the URL fails to load — always include it. To attach a user-uploaded file, hit `POST /api/workspaces/:slug/upload-image` from the human-side UI first to get a Vercel Blob URL, then reference that URL in the doc markdown. - A **lone video-file URL on its own line** (extension `.mp4` / `.m4v` / `.webm` / `.mov` / `.mkv`, signed-params + timestamp fragments tolerated) → native HTML5 `<video controls preload="metadata">` player. Source URL is referenced directly: no iframe, no transcoding, no quality loss. Vercel Blob is the canonical hosting (5 GB per file, served with HTTP range requests so 4K masters stream cleanly), but ANY publicly-reachable HTTPS URL works. Sample shape: a paragraph containing only `https://cdn.dock.ai/2025-launch-walkthrough.mp4`. Mid-paragraph URLs stay as plain links — surrounding prose disqualifies the auto-promotion (matches the oEmbed convention). - **```mermaid** fenced code → diagram (15 sub-types: flowchart, sequence, gantt, ER, state, class, mindmap, timeline, pie, quadrant, sankey, XY-chart, packet, block, journey) - **$x$** inline math, **$$x$$** block math (LaTeX, KaTeX-rendered, scripts/href disabled) - **> [!NOTE]** / **[!TIP]** / **[!IMPORTANT]** / **[!WARNING]** / **[!CAUTION]** GFM-style callouts - **```svg** fenced code → sanitized SVG embed (the universal escape hatch for custom diagrams; scripts and event handlers stripped at write time) - **<details><summary>X</summary>BODY</details>** → collapsible toggle - **[[slug]]** / **[[org/slug]]** / **[[slug#tab]]** / **[[slug#row-id]]** / **[[slug|display]]** → cross-references to another workspace, surface, or row. Resolved against your accessible workspace set; targets you can't see render as plain text on the reader's side (no info leak). Every cross-ref creates a Backlink row so the target's 'referenced from' sidebar shows this doc. - **[@Label](dock:mention/<kind>/<id>)** → @-mention of a user or agent. `<kind>` is `agent` or `human`; `<id>` is the principal id. Optional query params `?org=<slug>` (agents) or `?email=<addr>` (humans) for renderer hints. Mentioning a human writes a `doc_mention` row to their inbox + sends a deep-link email; mentioning an agent fires the `doc.mention_added` webhook so the agent service can wake up and reply. Re-saving a doc that already mentions someone does NOT re-fire — only newly-added mentions notify (computed from a diff against the previous body). Use this from agent code to ping a teammate when a doc you wrote needs their eyes. - A **lone URL on its own line** from a safelisted provider (YouTube, Vimeo, Loom, Figma, CodePen, GitHub gists) → sandboxed iframe embed. Other URLs stay as regular links. Surrounding prose disqualifies the auto-embed. Per-format caps: max 50 Mermaid diagrams (30 KB source each), max 500 math expressions (8 KB source each), max 50 SVG blocks (100 KB source each post-sanitize), max 200 cross-refs per doc, max 500 @-mentions per doc, max 20 embeds per doc, max 20 videos per doc (5 GB per file at upload time), max 200 images per doc. See /docs/doc-formats for examples. Last-write-wins; no CRDT merge. Emits doc.updated + doc.heading_added + doc.mention_added events as applicable. Requires editor role. Multi-surface workspaces optionally accept `surface_slug` to write to a specific doc tab; omitted writes the primary doc surface. Append-only updates have a dedicated `append_doc_section` tool that doesn't require fetching the body first.
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  • youtube_delete_video

    dialogbrain

    Permanently delete a YouTube video by id (or 'youtube:video:<id>'). Cannot be undone. Costs 50 quota units. Caller must own the channel.
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  • shillbot_verify_task

    Swarm Tips — Aggregated AI Agent Activities

    [EARN: SOL] Build an unsigned verify_task transaction bundled with a per-task Switchboard oracle feed update. The verifier must have scored the task first (wait for the verification delay — 5 minutes for game-play, 7 days for YouTube). Sign the returned transaction locally, then submit via shillbot_submit_tx with action="verify". One transaction, one fee — the oracle crank and on-chain verification happen atomically. Optional `network`: 'mainnet' (default) or 'devnet'.
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  • transcribe_chapterize_media

    mcp-knowledge

    Transcription and chapterization of long-form media (YouTube, podcasts, direct audio/video) for content marketing teams, podcast publishers, edu tech, journalists and accessibility/compliance. Pipeline: • YouTube → timedtext captions (keyless) + oEmbed metadata + native timecode chapters from description • Podcast RSS → episode description + duration + timecodes if embedded in show notes • Direct media → partial (requires Whisper API via OPENAI_API_KEY + force_whisper:true) • Chapters: native YouTube timecodes preferred; heuristic TF-IDF segmentation as fallback • Summary: extractive TF-IDF top-sentences (no LLM required) • Language detection: character-set heuristic (CJK→zh, kana→ja, hangul→ko, accents→fr/de/es) Output formats: json (full structured object) | text (plain transcript) | srt | vtt SLA: ≤15s budget total. Cache: 24h TTL.
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  • analyze_account

    hooklayer

    Deep intelligence on a TikTok or YouTube creator by handle. Returns viral DNA scores (viral_dna_score, replicability_score, originality_score, consistency_score, audience_fatigue), format fingerprint, top 5 recent videos with metadata (and transcripts on TikTok), content gaps, AND a `recommended_chain` field with pre-filled next tool calls. USE WHEN the user references a creator by @handle, asks "analyze X", wants competitor research, or needs creator context before generating content. The recommended_chain suggests which tools to call next (match_voice, trend_pulse, viral_remix) with parameters pre-filled — review and execute them as appropriate. Supports platform: "tiktok" (default, full transcript extraction) and "youtube" (channel Shorts analysis; transcript extraction lands in v1.1, current YouTube responses surface a partial-data flag noting this). Costs 5 credits. 1-hour cache per (handle, platform). TOOL HEALTH: Every response includes a `quality` field with a level (full | partial | degraded) and a reason. If quality.level is partial or degraded, you MUST flag this to the user explicitly in chat (e.g. "Heads up — this call returned partial data: <reason>") before reporting any results. Never silently route around a degraded response. REPORTING: When you summarize this in chat, you MUST surface viral_dna.viral_dna_signals, viral_dna.replicability_signals, viral_dna.originality_signals (each as bullet lists with the cited evidence string verbatim) AND viral_dna.would_fail_because verbatim AND provenance.video_post_dates so the user can see freshness. Never hide the evidence array behind a paraphrase — these are the auditability layer.
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  • shillbot_submit_work

    Swarm Tips — Aggregated AI Agent Activities

    [EARN: SOL] Submit completed work for a claimed Shillbot task. Provide the content_id (YouTube video ID, tweet ID, game session ID, etc.). Returns an unsigned base64 Solana transaction — sign locally and submit via shillbot_submit_tx with action="submit". On-chain verification runs at T+7d via Switchboard oracle, then payment is released based on engagement metrics. Optional `network`: 'mainnet' (default) or 'devnet'.
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  • youfiliate_delete_smart_link

    Youfiliate Smart Links

    Delete a smart link permanently. The short URL will stop working. IMPORTANT: Always confirm with the user before executing this action. The `confirm` parameter must be set to true. This is a destructive action that cannot be undone — the slug becomes available for reuse after a cooldown period. Does NOT affect other links or YouTube descriptions. Common errors: - Smart link not found: check the ID. - confirm=False: you must set confirm=True after getting user confirmation.
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  • entity_profile

    Youtube

    Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).
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  • pipeworx_trending

    Youtube

    What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.
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  • transcribe_video

    SubDownload

    Start an AI transcription (Whisper) of a YouTube video. Use when the video has no captions, when fetch_transcript returned NO_CAPTIONS, or when the user explicitly wants an AI transcript. ASYNC — returns task_id + estimated_wait_seconds. Tell the user how long it will take, then call get_asr_task to check status. Do not poll faster than next_poll_after_seconds. Costs 5 credits on completion.
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  • get_video_info

    TubePull

    Fetch metadata about a YouTube video WITHOUT downloading it. Returns title, channel name, duration, view count, upload date, thumbnail URL, full video description, available video qualities, and the YouTube license type (Standard YouTube License vs Creative Commons). Use this tool when the user says things like: - "what is this YouTube video about" / "summarize this video" - "how long is this video" / "when was this uploaded" - "who made this video" / "what channel is this from" - "is this Creative Commons" / "can I reuse this" / "what is the license" - "what qualities are available for this video" Do NOT use this tool when: - The user wants to download, save, rip, extract, or convert the video — use download_video for that. Free to call — does not count against the user's download quota. Call this before download_video when you need to confirm the video exists, pick the right quality, or check licensing before downloading.
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  • fetch_transcript

    SubDownload

    Fetch the full transcript (subtitles/captions) of a YouTube video in any language. ALWAYS call this when the user shares ANY YouTube link (youtube.com, youtu.be, shorts). Also use when the user wants to: summarize a video, know what was said, quote or cite video content, translate video dialogue, fact-check claims, study a lecture or tutorial, extract key points, analyze speaker arguments, or any task involving the spoken content of a video. Pass save=true to also bookmark the video into the user's Library in the same call (upserts the meta row; when the result came from ASR fallback it also flags has_asr). Saves a follow-up save_to_library round-trip.
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