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650,225 tools. Updated 2026-10-13 00:09

"A guide to video editing" matching MCP tools:

  • Enumerate and inspect the validated operations scene_apply accepts — call this BEFORE reaching for scene_script. The DSL is large (mesh editing, booleans, lathe/loft/sweep, curves, UV unwrap, modifiers, materials, lights, cameras, render settings, geometry nodes, batch and query ops), so most modelling does NOT need raw bpy. No args: every namespace with counts. guide=true (or op="guide" for older connector catalogs): full operating guide. namespace="mesh": that namespace's operations. Repeated details are object.radial_array or object.array_along_curve (no "pattern" namespace). Use world.update for the environment; validation is the separate scene_validate tool. search="boolean": ranked matches. op="mesh.bevel": the full JSON Schema with types, ranges and defaults. Schemas are introspected from the validator itself, so they are always exactly what scene_apply will accept. Full schemas are returned once in structuredContent; format="text" returns them in text instead. This tool is READ ONLY and free — it queues no job, spends no compute and changes nothing — so it is always safe to retry, including after a transport-level error.
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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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  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.
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  • Mint a short-lived signed URL for uploading a video directly, when you do not have a public video_url. POST or PUT the raw video (or multipart "video" field) to the returned upload_url within 15 minutes, then pass upload_id to create-submission-tool.
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  • Start a pipeline run in the background and return its runId immediately. Video pipelines take minutes; poll get_run for progress. Runs consume account credits. `inputs` is keyed by entry node id (get_pipeline lists them as entryNodes): a Text Input node takes text, an HTTP Payload node takes a JSON value, and a File node takes a URL that overrides the file placed on the canvas, so a clipping pipeline can be pointed at a new source video per run without editing the graph. An entry node left out runs with the value saved on the canvas; one with nothing saved is refused, so pass it (or "" to leave it blank on purpose), and ask the user what it should say when the request does not tell you. A key that names no entry node is refused before anything runs or is charged. Before running a pipeline you built or changed in this conversation, call estimate_run_cost and wait for the person to accept the price. Every run renders every node again, so to add music, narration or captions to a video an earlier run made, pass its url from get_run outputs to assemble_video (musicPrompt composes a bed) or edit_asset rather than editing the pipeline and running it again.
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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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  • 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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  • Edit a previously generated video with a text prompt and optional reference images (video-to-video); runs on griffin-hd (720p, with soundtrack) and the output keeps the source video's duration unless you pass one. Pass the video `url` you received from `createVideo`, `createVideoFromReferences`, or an earlier edit - it must be a video you generated within the last 7 days; arbitrary external videos are not accepted. Optionally add up to 5 reference `images` (URL or base64) to guide the edit. The job result is the new video URL and its actual duration in seconds. Credits are held when the job is accepted; the final charge is rate × produced seconds, never more than for the duration you requested, and the difference (or everything, if the job fails or is cancelled) is refunded. Pass an optional `request_id` to tag the result so you can locate it later via listGenerations (type video). Related tools: `createVideo` to generate the source clip, `createVideoFromReferences` for reference-driven generation. Async generation job: returns `{id, status}` - poll `getApiJob` (job and credit contract: see the server instructions). Credits: credits/s × seconds, per model: Griffin HD 2/s, Eagle 2/s [LEGACY]; [LEGACY] models are scheduled for removal - do not use them for new work; see this endpoint's full pricing table in the API docs.
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  • 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|edit` 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), `edit` is a plain-text "[NNNN] words..." paragraph list for editing by hand. 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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  • Use when someone needs a published Rung occupation, resume-situation, or military-transition guide. Returns public guide facts, source pages, and browser handoffs. Do not use for live jobs, employer search, resume editing, qualification decisions, or private work history; never send personal or resume data.
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  • Mamanida's editorial buying guides for one storefront, in that storefront's own language. Called without `guide` it lists the published guides (metadata only: title, deck, meta description, pillar, topics, dates and the canonical Mamanida URL), optionally filtered by `topic`. Called with `guide` (the guide slug from the listing) it returns that one localized edition plus its structured body: paragraphs, headings, lists, comparison tables, callouts, links to other guides and category calls-to-action. A `category_cta` gives a `category_slug` you can pass straight to search_products, which is the intended guide → category → product path. Retailer and affiliate URLs are never returned.
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  • Generate a video from a text prompt, optionally driven by reference images (image-to-video, first/last frame). This is asynchronous: it returns a task_id you poll with get_task(platform='video'). Generation usually takes 30-180 seconds. Pass wait_seconds to have the server poll for you. Video generation is the most expensive capability here — confirm the prompt with the user before spending on retries.
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  • Return the user's personalization guide — how they want a person researched before you write to them. Call this only when you are going to personalize a message; follow the returned guide. When none is set, returns a note and you should fall back to the default research rules in the outreach craft skill.
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  • The published guides. With no slug: the list, newest first, each with its title, description, written date and address, optionally only those whose title, description or slug contain every word of q. With a slug: that guide in full, its body as markdown. A guide that is not published is not found.
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  • Start recording a video for a project (its newest main guide, or a specific guide_id), on the desktop or as a phone/tablet (device). Returns the run id; poll get_run until is_terminal. Credits are charged only when the video completes.
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  • Read the full text of a cooking guide from recipes-daily.com, as markdown. Call this when search_recipes lists a guide that answers the question — how or why something works in the kitchen, how to store or substitute an ingredient, how to use a piece of equipment — and answer from what it says rather than from memory, citing its URL. Pass the guide URL exactly as search_recipes returned it. For recipes, use show_recipes instead: a recipe is a page the person cooks from, not text to retell.
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  • Ask a question about one or more videos with visual analysis. Most effective on focused time ranges — use start/end to specify the segment to analyze. BEFORE calling this tool, read the reka://docs/guide resource for recommended workflows. In most cases, you should first: - search_videos to find WHEN something happens, then pass those timestamps here as start/end - segment_video to detect and locate specific objects - get_transcript to read what was said For single-video questions, pass video_id with start/end. For cross-video questions, pass videos — a list of video references with start/end each. For follow-up questions, pass conversation_id from the previous response. You can add start/end to drill into a specific moment while keeping the conversation context. Requires qa_only or full pipeline.
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  • Use this to create or edit an AI video. Text-to-video from a prompt; image-to-video by passing image (start frame, + optional end_image); reference-to-video by passing reference_images; or video-to-video editing by passing video (an input video URL — upload local files with upload_media first). IMPORTANT — cost: video is priced per SECOND and by resolution (default model seedance-2.5: 480p=150, 720p=330, 1080p=750 credits/sec, plus 80/160/375 per second of reference-video INPUT), so e.g. 5s at 720p ≈ 1,650 credits and 5s at 1080p ≈ 3,750; confirm with the user before expensive combos (long durations or many reference clips). Each call starts a new paid job, charged on success only. Submits an async job and returns a job_id (uuid) — video takes MINUTES: poll check_generation_status every 15–30 seconds until it returns the finished video link, then share that link with the user. Default model: seedance-2.5; call list_models for available video models and prices.
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  • Get the guide to authoring a wireframe mockup — the markup dialect, the wireframe component set, what the drawn style discards, and a complete valid example. Call this BEFORE composing your first mockup in a conversation: markup written from general Tailwind and HTML habits is refused, and the guide is what an author needs to write a mockup that is accepted first time.
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  • Read the FULL timeline of a video: every clip per track in playback order with clip_id, asset_id, name, kind, duration_sec, cumulative timeline_start_sec, and any non-default trim/speed/volume, plus all captions and the total video-track duration. This is what you need to SEE the actual layout/lengths before editing — get_state does not include durations. Reference clips by clip_id afterwards. Free, read-only.
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  • DESTRUCTIVE. Edit the CONTENT of an existing Meta ad: primary text, headline, description, CTA, destination link, display link, UTM url_tags, and the image/video itself. Meta creatives are immutable, so this builds a NEW creative and repoints the ad: the ad keeps its id but gets a new creative_id and the old creative is orphaned. Editing a live/spending ad can reset its social proof (likes/comments/shares) and restart the learning phase. Text fields are ARRAYS — send the COMPLETE set with your edits applied; entries you don't change are preserved verbatim. Media swaps use creative-library assets only and are like-for-like (image->image, video->video); for multi-image ads (square + vertical) use the `media` array, one entry per slot. ALWAYS call with dry_run: true first — the dry-run returns the before/after diff AND the current media slots (use those to build a media swap) — then dry_run: false to apply.
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