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470,768 tools. Updated 2026-08-23 13:09

"A guide to video editing" matching MCP tools:

  • Transcribe audio or video to text, including per-word timestamps for precise editing. Three-call flow: (1) call with `filename` to receive {job_id, payment_challenge}; (2) pay via MPP, then call with `job_id` + `payment_credential` to receive {upload_url} (presigned PUT, 1h expiry); (3) PUT the bytes, then complete_upload(job_id), then poll get_job_status(job_id). On completion, get_job_status returns two outputs: role `transcript` (SRT) and role `transcript-words` (JSON matching /.well-known/weftly-transcript-v2.schema.json, with segment-level and per-word timestamps). For other formats, pass `format=srt|txt|vtt|json|words` to get_job_status to receive content inline — `txt` and `vtt` are derived from SRT, `json` is v1 (segments only), `words` is v2 (segments + words). Flat price: audio $0.50, video $1.00 — see /.well-known/mpp.json for the authoritative table. Use for podcasts, interviews, meetings, lectures, and especially for creating clips, multicamera edits, or edit-video-from-transcript where word boundaries matter. Retrying any call with `job_id` alone returns current state (idempotent). Failed jobs auto-refund.
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  • Turn a script into a finished 1080p video — narrated, cut to matched stock footage, subtitles burned in, audio normalized to −14 LUFS. Returns a job id; poll get_job, then fetch_video. Use when you need a publishable video and have only text. $0.60 per video in USDC on Solana — no account, no API key, no human in the loop. script: narration body to speak (plain text) title: optional intro title shown for ~4s at the top voice: voice id from list_voices(), e.g. female_warm subtitles: burn-in subtitles (default true) speed: narration speed multiplier, e.g. 1.0 seed: stock-selection seed for reproducible visuals, e.g. 7
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  • Read the user's staged references in Switch Studio. Returns TWO groups: (1) the image-generation reference strip (typed face/body/outfit/scenery/product slots) under `refs`, and (2) the VIDEO-tab references the user staged in the Omni/Image video tabs (the @Image1/@Image2 strip) under `videoReferences`, with usable signed URLs. Call this before generate_image or generate_video whenever the user says "use my refs" or refers to images they staged in Studio (including "the images in my video tab"). To make a video from the video-tab refs, pass videoReferences.imageUrls into generate_video reference_image_urls (and videoUrls into reference_video_urls) in reference-to-video / omni mode. Refs marked alive:false are dead (stored file gone) and are already excluded from the usable url lists. NOTE: a photo the user just attached in THIS chat is in neither group — for that, call upload_media and use its returned url/asset id directly.
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  • 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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  • 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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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • 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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  • 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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  • Upscale a previously generated video to twice its resolution (2x). Pass the video `url` you received from `createVideo`, `createVideoFromReferences`, or `editVideo` — it must be a video you generated within the last 7 days; arbitrary external videos are not accepted. Only videos below 960x960 pixels can be upscaled (larger sources are rejected). Synchronous: the call blocks until upscaling finishes and returns the new video URL and its duration in seconds. Billed per second of video, independent of model, charged only on success. Pass an optional `request_id` to tag the result so you can locate it later via `getVideoResults`. Related tools: `createVideo` for image-to-video, `editVideo` to modify a generated video. Requires an API key (user scope). Credits: 0.2 credits per second of video.
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  • Read-only. Use to find workflows in a project by name, description, or trigger type before inspection or editing. Trigger filters include database, auth email, repeating, broadcast, and no-trigger workflows. Returns paginated workflow summaries, published/sandbox state, trigger type, workflow URLs, totalCount, hasMore, and nextOffset. Do not use as the final source of truth before editing; call get_workflow_and_preview_url for full structure.
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  • Step 2 of uploading a video: after the file has been PUT to the uploadUrl, call this with the uploadId to create the video record. Returns the video (muxPlaybackId will be 'pending'). Poll viddler_videos_get until muxPlaybackId resolves — processing usually takes under a minute. If title/description are omitted, AI generates them from the video content.
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  • Lists Picsart AI models across ALL modes (image / video / audio / text) and renders the Picsart Studio model-picker widget so the USER can browse, compare, and pick a model visually. Each item carries `id`, `name`, `mode`, `inputType`, `supportedAspectRatios`/`supportedResolutions` (when the model declares an enum for that param) (and `provider`, `badges`, `description` when `verbose` is true). Use this when the user wants to SEE the available models or pick one themselves — especially when they have not committed to an output mode yet, or for cross-mode searches ("all flux models", "every model with image input"). To narrow to one output mode without a separate tool, pass the `mode` filter (image/video/audio/text) on this same tool. Ratio/resolution constraints ride along in `supportedAspectRatios`/`supportedResolutions`, so you rarely need `picsart_model_params` just to check whether a model supports a given aspect ratio or resolution. Do NOT use it to fetch a single model's FULL parameter schema (use `picsart_model_params`) or estimate per-call cost (use `picsart_preflight`). If you only need catalog knowledge for your own reasoning (no UI shown to the user), use `picsart_model_catalog` instead. Inputs (all optional): `mode` (filter to image/video/audio/text — text = LLM models that return generated text), `provider` (case-insensitive substring like "flux", "kling", "google"), `acceptsImage` (true → only models that take an image input — i2i, i2v, i2t), `acceptsVideo` (true → only models that take a video input — v2v, v2a, v2t), `acceptsAudio` (true → only models that take an audio input — a2v, sts), `inputType` (exact-match escape hatch; one of t2v/i2v/v2v/a2v/t2i/i2i/t2a/v2a/tts/sts/sfx/music/t2t/i2t/v2t), `limit` (1–100, default 20), `verbose` (default false; when true each item adds provider/badges/description). inputType codes — first letter is input modality, second is output: t2i (text→image), i2i (image→image), t2v (text→video), i2v (image→video), v2v (video→video), a2v (audio→video), t2a (text→audio), v2a (video→audio), tts (text-to-speech), sts (speech-to-speech), sfx (sound effects), music (music gen), t2t/i2t/v2t (LLM text output from text/image/video input). Example: `{ mode: "video", acceptsImage: true, limit: 10 }` returns image-to-video models. Returns `{ items, total, truncated }` — `truncated` is true when more matched than were returned; refine filters or raise `limit` (max 100) to see more. Read-only; spends no credits and works without authentication.
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  • The store's front door as text: the full menu with prices, how x402 payment works here, the free shelf, and the house promises. Free. Completes when the guide text returns. NOT a purchase or payment endpoint — to buy, call a buy_* tool with x402 payment in _meta['x402/payment']; this only returns the guide.
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  • Correct a lot the USER already recorded: a mistyped quantity, price, trade date or note. Only the fields you pass change; the rest are left alone. The instrument itself cannot be edited: a lot on the wrong stock or the wrong contract is a different holding, so remove it with RemovePortfolioLot and add the right one. To record a sale, use ClosePortfolioLot rather than editing the quantity down, because editing it away loses the realized profit.
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  • Edit an existing video from a prompt, or transfer motion onto a subject image. Pass the source in video_url and the change in prompt. Defaults to Google Gemini Omni video edit; switch with model ('kling-edit', 'wan-edit', or 'motion-control' for Kling motion transfer with a subject image in image_urls). This is for changing an existing clip — to make a new video from scratch use generate_video, to extend one use extend_video, to upscale use upscale_media. Returns the video URL.
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  • Switch Vision — watch and understand a video (or image) like a human and answer a question about it: scenes, subjects, actions, on-screen text, pacing, mood and sentiment. Pass video_url (a public https video URL, including YouTube) OR one of your own Switch videos (a video/asset id from list_my_videos / list_my_assets / upload_media). Add an optional question to focus the analysis (e.g. "what is the tone and energy?", "list the cuts and what each shot shows"). Use this whenever the user gives you a reference video and wants its style, energy, structure or content understood — for example before making a new video that matches it.
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  • Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.
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  • Input: A muted video URL along with a textual prompt describing the desired audio. Output: We will return the video URL with the applied audio. Functionality: This tool now takes a muted video and a text prompt as input. It generates an audio track based on the provided prompt and applies this audio to the video, resulting in a video with integrated sound. Steps: 1. We will get the user_id from the request context. 2. We will validate the user's generation tokens. 3. We will call the Audio Application API with the muted video URL and the provided prompt. 4. The API will generate the audio from the prompt and merge it with the muted video, returning a JSON response with the updated video URL. 5. We will return the updated video URL to the user. INSTRUCTION FOR CLIENT MODEL: - Extract the required input parameters 'video_url' (type: string, URL) and 'prompt' (type: string, describing the desired audio) from the user's prompt. - Ignore any extraneous information in the user's input. - Pass the extracted values to this tool as 'video_url' and 'prompt'. - Example: For user input "Add dramatic orchestral music to this video https://example.com/video.mp4", extract 'video_url' as 'https://example.com/video.mp4' and 'prompt' as 'dramatic orchestral music'.
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  • Generate Switch video across the real provider lineup (Kling, Seedance, Switch Video/WAN 2.7, Switch Video Edit, Topaz upscale) and modes (text-to-video, image-to-video, frame-to-frame, motion, omni, reference-to-video, video-edit, upscale). ALWAYS call list_video_models first to pick the right model + mode and see its required inputs. Pass one shot, or shots:[...] for a storyboard (max 4 by default, hard max 10) where EACH shot is DIFFERENT — never repeat one prompt to get copies. Renders async (~30-90s); a background job delivers each clip to your library. Returns a task_id per shot — poll get_video_status or list_my_videos.
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  • Stitch several of your Switch videos together into ONE video, played back-to-back in the order you give. Pass clip_asset_ids: an ORDERED list of your video ids (get them from list_my_videos) — the first id plays first. Optional orientation (landscape|portrait|square), fps, quality. Renders the combined video with ffmpeg and returns the finished, downloadable video url right away (also saved to list_my_videos). Use this whenever the user wants to combine, join, merge, or concatenate multiple clips into one.
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