"A tool for extracting video script content" matching MCP tools:

• lamina_generate_video

  lamina

  Dispatch a single atomic video generation. Sibling of `lamina_generate_image` — same shape, but outputs a video URL. WORKFLOW: (1) `lamina_models_list({ modality: "video" })` → pick a model. (2) `lamina_models_describe({ modelId })` → read its flat `paramSchema` to learn required inputs. (3) `lamina_generate_video({ model, prompt, params })` → dispatch, get runId. (4) `lamina_status({ runId, wait: true })` → poll until completed; the response has `output.url`. ONE TOOL, EVERY VIDEO OPERATION. Model id selects the operation; `params` matches the model's paramSchema: • Text-to-video — Kling t2v variants, Wan-2.6-text-to-video, Wan-turbo, Minimax, Seedance t2v, Veo3-text-to-video. Just `prompt` (+ duration / aspectRatio / etc. per the model). • Image-to-video — Kling i2v variants, Wan-2.6/turbo image-to-video, Minimax i2v, Seedance i2v (uses `startImageUrl`), `happy-horse-image-to-video`, `veo3-image-to-video` (sync). `params` includes `imageUrl` (or `startImageUrl` for Seedance, `firstFrameUrl` for Veo3 first-frame). • Keyframe — `veo3-keyframe-to-video` (sync). `params` requires `firstFrameUrl` AND `lastFrameUrl` — model interpolates between them. • Motion-control — `kling-v26-motion-control`, `kling-v26-motion-control-pro`. `params` requires `imageUrl` (character) AND `videoUrl` (motion reference). • Video-to-video (edit) — `wan-video-to-video`, Kling v2v variants. `params` requires `videoUrl` (source). • Reference-to-video — Kling/Seedance/Wan reference variants. `params` uses `referenceImageUrls`. INPUTS: • `model` (required): a model id from `lamina_models_list({modality:"video"})`. • `prompt`: most models require it; some (motion-control variants) are optional. Check `paramSchema.prompt.required` from `lamina_models_describe`. Some models omit `prompt` from `paramSchema` entirely (prompt-less). • `params`: model-specific fields per the model's `paramSchema`. Required URL fields vary by operation — see list above. • `webhookUrl` (optional): HTTPS URL for HMAC-signed completion POST. • `includeCitationKit` (optional, PREVIEW): set `true` to request a citation-ready kit alongside the video — cleaned transcript, question-formatted chapters, a 30–60 word summary, and drop-in `VideoObject` JSON-LD — so wherever you host the video it is answer-engine-citable. Preview signal only: it records interest and returns a `coming_soon` note; the kit is not yet produced. RESPONSE: `{runId, status: "queued"|"completed", model, mode, prompt, resolvedParams}`. `mode` is the resolved operation. Pass `runId` to `lamina_status`. If `includeCitationKit` was set, the response also carries `citationKit: {status: "coming_soon"}`. SYNC vs ASYNC: identical contract. Veo3 variants (`veo3-text-to-video`, `veo3-image-to-video`, `veo3-first-frame-to-video`, `veo3-keyframe-to-video`) are Vertex-backed and complete in seconds. fal-backed models queue and take 30s–5min. `lamina_status({ wait: true, timeoutSeconds: 240 })` handles either transparently. ERROR HANDLING: same shape as `lamina_generate_image` — `code` + `details.errors[]` with `field` + `allowed`/`range`/`got`.

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• lamina_compose_video

  lamina

  Compose a NARRATED, MULTI-SHOT video from a script — NOT a single ~5s clip. Use this when you need a coherent minute-ish demo / explainer with voiceover: it synthesizes the narration, storyboards it into beats, generates a continuity-chained shot per beat, and renders with transitions + Ken-Burns + captions via Remotion. (For a single short clip, use `lamina_generate_video`.) WORKFLOW: (1) `lamina_compose_video({ script })` → dispatch, get `runId`. (2) `lamina_compose_video({ runId, wait: true })` → block until done; or poll `{ runId }`. Composition takes minutes. INPUTS: • `script` (required to start): the narration to speak (a hook + one insight + a CTA; ≤~90s). The transcript/chapters derive from this, so the video stays coherent with its text. • `title` / `generationBrief` (optional): title + a one-paragraph visual brief for the shots. • `direction` (optional): free-text creative direction ("open on the product, fast cuts, end on the logo") — steer the render WITHOUT naming models. • `sections` (optional): structured per-span hints `[{ text?, hint, mustShow? }]` for a prescriptive storyboard. • `format` / `inputs` (optional): pick a format (else auto-routed); `inputs` supplies a format's required assets (e.g. `{ presenterImage }`). • `aspectRatio` (optional): `16:9` | `9:16` | `1:1` | `4:5` | `4:3` (default 16:9). • `voiceId` (optional): ElevenLabs voice id. Omit and the narration director picks a voice whose tone fits the script. • `expressive` (optional): true → adds v3 audio tags for stronger, more human inflection. (Prosody/pacing is always applied.) • `idempotencyKey` (optional): dedupe retries — the same key returns the same run (no double charge). • `runId` (+ optional `wait`): pass a prior runId to poll instead of starting a new run. TIP: call `lamina_compose_plan({ script })` first to preview the format + cost + storyboard for free before committing. RESPONSE: dispatch → `{ runId, status: "running" }`. Poll → `{ status, progress: { stage, current?, total? } }`. Terminal → `{ status: "completed", result: { videoUrl, durationSeconds, shotCount } }` or `{ status: "failed", error }`. Invalid input → an error with a machine-readable `reason` (e.g. `MISSING_REQUIRED_INPUT`, `SCRIPT_TOO_LONG`).

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• make_explainer

  Hermoso

  Turn a TOPIC into a finished narrated, captioned explainer video. Writes a sectioned script, paints one image per section, narrates each with TTS, adds gentle Ken-Burns motion, then composites the on-screen text + end card with the Chrome+ffmpeg engine the ads use (text is never model-painted, so it never garbles). It is an image-slide film WITH motion, not N video-model renders — that's what keeps it affordable. `style` picks the visual family: the default 'cinematic' is photoreal editorial; every other id is a STYLED, strictly non-photoreal look (illustrated / collage / clay / pixel …) that first renders ONE style-key image and then locks every scene to it, so the whole film holds one look. Cost: a ~31-credit hold for a ~6-section 60s explainer on the default style; a styled one renders that extra key and routes each scene through the compositing model, so budget a hold of up to ~58 credits for the same 6 sections. Both settle to the exact per-section image + narration spend (a longer target = more sections = more). Needs the writing model and a narration voice engine connected. NOT the tool for a short product ad — use render_ad or generate_video for those, and make_template_ad for the deterministic native formats.

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• bannerbear_create_video

  bannerbear

  Generate a video from a video template (additive; CONSUMES API quota). Async: returns a `pending` video whose uid you poll with bannerbear_get_video (video_url populates on completion). API: POST /v2/videos.

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• detect_script

  Indic Normalize

  Detect the dominant script of input text. Returns primary script + per-script character counts + a confidence score.

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• viral_remix

  hooklayer

  Take a viral video and produce a fresh script that mirrors its structure and energy pattern for a new topic. Returns the extracted formula, scene-by-scene script with voiceover and visuals, camera directions, and text overlays. Use when the user finds a video they want to replicate the structure of. Pass either a video URL (TikTok, YouTube, or Instagram) or a transcript directly.

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• predict_virality

  hooklayer

  Score a draft script for viral potential with adversarial verification. Returns a virality score, recommendation (ship/rework/no-go), viral DNA breakdown with evidence, attack vectors analysis, and calibration metrics. Use when the user has a finished draft and wants pre-publish verification. Pass either a script string or a video URL.

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• web_url_reader

  Inferventis — Financial Data, News & Web MCP

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

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• lookup_native

  RedM Mcp

  Resolve a RedM/RDR3 SCRIPT native by hash or name — O(1), exact. Use whenever you see `Citizen.InvokeNative(0x...)`, `Citizen.invokeNative('0x...')`, `GetHashKey('NAME')`, or a SCREAMING_SNAKE_CASE native name (e.g. `SET_ENTITY_COORDS`, `GetPedHealth`) in Lua/JS/TS. NOT for game-data hashes (weapon/ped/animation names) — use `grep_docs`. Pass `hash` (0x… optional, case-insensitive) or `name` (exact first, ILIKE substring fallback). Returns name, hash, namespace, return type, params, description, full content, plus `findings[]` — community gotchas linked to that native. Inspect `findings[].id` and call `get_document({path: 'learning:<id>'})` for full body. Also returns `refDocs[]` — enum/flag value tables for that native (the constants to pass for params like flagId/attributeIndex/eventType). When `refDocs[].content` is set, it's the inline enum table — use those values directly. When `content` is null but `refDocs[].fetch` is present, the table was too large to inline — run that exact call (e.g. `get_document({ path: "refdoc:eEventType" })`) to get the full table; `refDocs[].preview` shows the first lines. github entries (no `fetch`) are url-only.

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• voice_intelligence_run

  StackFast FractWin Expert Brain

  Run the voice intelligence orchestrator over any input: an uploaded or recorded audio/video file (base64 in file), a public audio or video URL (audio_or_video_url), a PDF (pdf), an image (image), or raw text/notes (text and/or notes). Provide exactly ONE input carrier — audio_or_video_url, file, pdf, image, or text/notes. The input is normalized to a transcript via the existing transcription rails, then three composed outputs are returned: a condensed summary (with action items, decisions, and a next step), a full-verbatim polished actual script (filler removed, wording preserved, never paraphrased; call sources return a masked summary instead), and an authority report (content flywheel plan, plus an owner-facing business report when business context is provided). All outward outputs are mask-gated.

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• get_upload_url

  Botverse

  Get a presigned upload form for any file — video, audio, or document (markdown, HTML, DOCX, etc.). It expires in 15 minutes. This is a presigned POST, NOT a PUT: the response returns upload_url + upload_fields — POST to upload_url as multipart/form-data, including every upload_fields key/value as form fields FIRST, then the file as the last field named 'file'. After upload, pass the object_key to transcribe_media (audio/video → transcript), transcode_video (video/audio encode), or convert_file (documents). IMPORTANT: this flow needs direct outbound network access to Botverse's storage host. In sandboxed agent environments (claude.ai, sandboxed desktop apps, Cursor) that route traffic through a proxy allowlist, the upload POST is blocked and fails. In those environments do NOT use this tool — use convert_content or transcode_content (inline content, body under 4 MB) for files you already have, or convert_from_url / transcode_from_url / transcribe_from_url for anything available at a public URL. Neither needs an upload step.

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• youtube_transcript

  youtube-media-mcp-server

  Extract transcript/subtitles from a YouTube video. Args: video_url: YouTube video URL (e.g. 'https://youtube.com/watch?v=...') language: Language code (default 'en')

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• files_read

  DialogBrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• youtube_video_query

  DialogBrain

  Ask Gemini about a YouTube video. Pass a video URL and any prompt — verbatim transcript with timestamps, summary, targeted Q&A about content or visuals, translation, etc. Works on any public/unlisted video.

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• web_fetch

  DialogBrain

  Fetches a single URL and returns its content. Use this when you have a specific URL in mind — for example, after web.search returns a link you want to read, or when the user pastes a URL. Modes (extract): - 'auto' (default): picks the right mode based on response content type. - 'markdown': for HTML pages; returns cleaned markdown plus the page <title>. - 'text': for JSON/XML/plaintext APIs; returns the raw decoded body. - 'file': for images, PDFs, audio, video, archives, or any binary — ingests the bytes into the user's file storage and returns a file_id you can pass to messages.send (to send as an attachment), agents.add_file (to add to agent knowledge), or files.read. Use web.fetch (not files.upload) when you need the file_id immediately for the next tool call — files.upload(source_url=…) is async and won't have the file ready in the same turn. Use web.search (not web.fetch) when you don't have a specific URL yet and need to find one.

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• artifacts_export_pdf

  DialogBrain

  Snapshot an artifact's current version to a PDF saved in the workspace. NOTE: the PDF is a STATIC capture rendered with JavaScript disabled — interactive or JS-drawn content (charts on <canvas>, script-generated SVG) will not appear. Author charts as static SVG if they must show in the PDF. Returns the file_id; deliver it with messages.send(attachments=[file_id]).

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• agent_video

  agentic-commerce-catalog

  Generate a fully owned short-form music-video clip for a song, product, or campaign. Renders creator-owned video you can pair with Suede's full-length song endpoints. Async callers (?async=true or PAYMENT-SIGNATURE-authenticated requests, which auto-async) get back a jobId and pollUrl; poll GET /agent/video/{jobId} — no additional payment required — until status is 'completed' and videoUrl is set. — $6.99 USDC via x402 on Base (chain 8453).

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• get_my_active_references

  switch

  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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• generate_video

  switch

  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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• talking_avatar_video

  switch

  Turn a face photo into a lip-synced talking-head video that speaks your text (or your audio). Provide image_url (a clear face photo) and either script (text to speak, max 2500 characters) or audio_url. Optional voice_id / language / voice_settings. Renders in ~1-5 minutes (single call, returns the finished branded video) and is saved to your library. Charged per video.

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