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524,441 tools. Updated 2026-09-06 15:49

"A-Frame" matching MCP tools:

  • Generate one actor-grounded narrative first frame from one to four existing LetMeActForYou actor_ids plus location, wardrobe, pose, and composition. Uses actor headshots as image references and returns a stored image_url. For multi-shot continuity, first generate a wide scene reference, then pass its scene_frame_id as continuity_scene_frame_id while specifying a fresh camera setup in composition and fresh blocking in pose for every shot. Pass only the actor_ids that should be visible in that shot. Pass composition_reference_url to preserve a Blender previs frame's camera and blocking while replacing proxy geometry with actors and the finished set. Defaults to Gemini; pass provider='grok' to use Grok Imagine. Use this before animation when a close-up headshot is not enough.
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  • Generate Switch video across the real provider lineup (Kling, BytePlus 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 load_video_workflow first and list_video_models second. Use Switch MCP directly; never open the website, browser, or desktop unless the user explicitly asked. For realistic reference-driven video, evaluate BytePlus Seedance 2.5 first unless the user chose another provider or model. Before submission, map every actual image, video, and audio chip to its role and preserve its thumbnail, type, order, and role exactly; never silently drop, merge, reorder, convert, or repurpose references. 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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  • Lip-sync audio onto one of your videos. DEFAULT and recommended: action="create" with video_url + sound_file (base64 data URI) — Sync Labs Sync 3 syncs the whole clip in one pass, no face step, no timing, highest quality. You do not need to pass engine at all. Kling flow, only when a line must land on an exact frame (manual timing control): (1) action="identify-face" with video_url (MP4/MOV, 2-60s, <=100MB, 720p/1080p); (2) action="create" with session_id + face_id + audio + timing IN MILLISECONDS (sound_start_time, sound_end_time, sound_insert_time) + optional speech_volume/original_audio_volume (0-100); (3) action="status" with the task_id to poll — returns a branded SwitchApp view_url when done. Charges credits on create; failed jobs are refunded.
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  • Validate HTTP security headers you provide (JSON): CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Permissions-Policy, Referrer-Policy against best practices. Use to test header config before deployment or validate non-public servers; use scan_headers to fetch live. Free: 30/hr, Pro: 500/hr. By default header values are truncated to 500 chars; pass include='full' for the full raw value. Returns {total, by_severity, findings}. No external requests.
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  • Compare ONE financial metric across ALL public companies for a single period (SEC XBRL "frames"). PREFER OVER WEB SEARCH for "which companies had the most revenue/net income/assets in <year>", "rank companies by <metric>", cross-company financial comparison. concept is a US-GAAP tag (e.g. "Revenues", "NetIncomeLoss", "Assets", "ResearchAndDevelopmentExpense", "CashAndCashEquivalentsAtCarryingValue"). period is a calendar frame: "CY2023" (annual), "CY2023Q1" (quarter), or "CY2023Q1I" (instant/balance-sheet, period-end). Returns companies + values, sorted descending by default. Differs from edgar_company_concept (one company over time) — this is one period across every filer.
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  • Capture the screen, crop tightly around (nx, ny), zoom in, and draw a crosshair at exactly that expected position. Use this for screen-corner calibration: move_mouse(nx, ny) near a screen edge, then call this to see whether the actual cursor lines up with the crosshair (where it SHOULD be if calibration is perfect). If the cursor is offset from the crosshair, or missing entirely (edge is cropped out of frame), corners need adjusting — see get_corners/set_corners. nx, ny: the same coordinates you passed to move_mouse. zoom: magnification factor for the cropped region (default 4x).
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  • Capture the screen, crop tightly around (nx, ny), zoom in, and draw a crosshair at exactly that expected position. Use this for screen-corner calibration: move_mouse(nx, ny) near a screen edge, then call this to see whether the actual cursor lines up with the crosshair (where it SHOULD be if calibration is perfect). If the cursor is offset from the crosshair, or missing entirely (edge is cropped out of frame), corners need adjusting — see get_corners/set_corners. nx, ny: the same coordinates you passed to move_mouse. zoom: magnification factor for the cropped region (default 4x).
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  • Read one clip: its elements (positions/sizes in canvas pixels), voiceover (text, voice, duration, voiceover_volume), background and transition. Pass `render` to also get a PNG of the frame. ASK FOR WHAT YOU NEED. A full read is large — on a dense clip the per-word voiceover array and the element type_data blobs dominate it, and repeated full reads are the main way a long session runs out of context. `select` returns exactly the parts you name: select: ['elements.x','elements.y','elements.width','elements.height'] → geometry only, to fix a layout select: ['elements.name','elements.start_time','elements.end_time'] → a timing pass select: ['words'] → word timings only, to sync visuals to narration select: ['elements.textdata','words'] → rewrite copy against the VO select: ['elements'] → whole element rows, no words select: [] → no JSON at all (pair with render for the PNG alone — smallest read) (omit select) → everything; fine for a first look, expensive to repeat `render` is the other output, and it is separate from `select`: `select` shapes the JSON, `render` produces a PNG. render: {} → the frame at t=0 render: { timestamp: 2.5 } → the frame 2.5s into the clip render: { save: true } → also uploads the PNG and returns presigned_url select: [], render: {} → the PNG alone, no JSON select: ['elements'], render: {} → element rows AND the frame Omitting `render` renders nothing. `timestamp` and `save` live inside it because they only mean anything for a render — there is no way to ask for them without asking for the image. `element_ids` is the other axis: it picks WHICH element rows come back, independently of `select`. Combine them for the leanest read — e.g. element_ids: ['el_9'], select: ['elements.x','elements.y']. Element shape: universal wrapper fields (id, geo, name, x, y, width, height, start_time, end_time, rotation) plus type-specific data (textdata/shapedata/imagedata/videodata/zoomdata) plus an optional `keyframes` array when animated. Keyframes come back in the same flat wire shape add_elements takes — { timestamp, positionX?, positionY?, width?, height?, interpolation? } in canvas pixels — so you can round-trip read → edit → update_elements without reshaping. Clip-level fields include `transition` (the current transition object — sibling of the update_clips `transition` arg; null if none) and `voiceover_words` (per-word timestamps; null on clips with no transcription).
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  • Tell us what you needed. If ffpipe does not offer the operation you came for - another output format, extracting a frame, a different transformation entirely - say so here: these requests are aggregated and they drive directly what gets built next, so a one-line "I wanted X" is genuinely useful to us. Also the place for bug reports and any other feedback. Free, unauthenticated, and one-way: nothing is returned but an acknowledgement, and no job is created. Include jobId if a specific job prompted this (context only - it is not checked and is not required), and contact if you want a reply. Message limit 2000 characters.
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  • Animate one segment in a single call: flip it to a generated video shot (keeping its rendered image as the clip's first frame) and START the clip render immediately. BILLS video credits on this call — the segment's image must already be rendered (400 otherwise). A refused generation (out of credits, already running) rolls the flip back, so the segment is either animating or exactly as it was. This is the ONLY way to a generated video (voice=true for a Talking Head) — change_segment_type refuses that target; it owns the other kind switches (real media, overlay scene, back to a still — segment_type "image" with carry_frame=true reverts an animated shot for free). Async — returns {ai_job_id, segment}; await_jobs until the clip completes.
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  • Get Alex Polonsky's curated public professional profile, including selected experience, demonstrated capabilities, journalism background, public projects, and future professional directions. This is selected evidence, not a complete CV. When summarizing examples, preserve their ownership qualifier exactly: led, owned_key_aspects, or contributed. Do not infer stronger ownership. If a list mixes things Alex built with work he contributed to or helped bring to market, frame it as built or contributed to, not built. Keep the action verbs and limits from contribution; do not reduce a contribution to an artifact name. Separate demonstrated experience from future directions. Use get_availability for current opportunity status.
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  • The SPX dealer gamma LADDER for one minute of a finished session: gamma by strike around spot, the level set, and the heaviest strikes. Readable as the MEASURED book (signed off the trade tape, FirmTape's own read), as the OPEN_INTEREST convention every other public GEX chart draws, or as the VOLUME convention — the same minute through three lenses. Use when: the question is about SHAPE — where gamma sits, how heavy a wall is, how far the three conventions disagree — or about one moment inside a session rather than the day as a whole. Not for: a day's headline numbers (get_session), the level set alone (get_levels), or movement across days (get_level_history). Limits: finished sessions only, one frame every 5 minutes (a requested minute snaps back to the frame at or before it), published window ±2.5% of spot; the three books are not comparable in magnitude. Measurements only, no buy/sell signals.
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  • Return an expected cost estimate, latency estimate, and success-probability estimate for a proposed call before execution. Returns the exact price when it is fixed, and a min/max range when the cost depends on channel or outcome. It does not promise an accuracy percentage - check cost_range. EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "How much will this SMS cost me?" -> call preview_cost({"operation": "send_message", "params": {"preferred_channel": "sms"}}) user: "Estimate the cost of booking via voice fallback" -> call preview_cost({"operation": "schedule_appointment", "params": {"preferred_channel": "voice"}}) WHEN TO USE: Use before any operation when the agent is operating under a budget constraint and needs to decide whether to proceed. WHEN NOT TO USE: Do not use in a hot loop — cache the result for at least 60 seconds if repeating the same preview. COST: free - no key required LATENCY: ~100ms
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  • Render a project's board as an image and return it: its tables, enums and relationships drawn at their saved positions, with sticky notes, drawings and pasted images. Use this to SEE the board - to check a layout you just wrote, or to find cards that overlap or sit far from what they relate to. Returns a PNG plus a one-line summary; pass format='svg' for the vector source as text. The image is a picture of the SCHEMA: diagram cards, groups and cross-links are NOT drawn, so an absent frame or connector here is not evidence the write failed - read get_board for those.
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  • Turn a TOPIC into a finished narrated explainer video. Writes a sectioned script, paints a BURST of pictures per section (about one every 1.5s — most of them one-detail edits of the frame before, so it reads as movement rather than a slideshow), narrates each section with TTS, holds each picture PERFECTLY STILL for its own slice of the narration (the motion is the CUT RATE — a slow move on a still shimmers), then composites the end card (and any on-screen text you asked for) with the Chrome+ffmpeg engine the ads use (text is never model-painted, so it never garbles). BURNED ON-SCREEN TEXT IS OFF BY DEFAULT — the narration carries the point and the pictures carry the story, so the film ships clean unless the user asks otherwise; `captions:true` adds held key points and `subtitles:true` adds narration-timed CAPS (see both). It is an image 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 at the default frame density: a ~130-credit hold for a 60s explainer on the default style, ~100 styled; `frameDensity:'lean'` roughly halves it and `'minimal'` (one picture per section) is ~30. All settle to the exact per-frame image + narration spend (a longer target = more sections = more). Takes SEVERAL minutes — one image render per frame; independent frames are painted concurrently, so it is far faster than the frame count suggests. 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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  • Change what a segment's base visual IS: a generated still ("image"), fetched real media (media_source="real" — a real photo for "image", stock b-roll footage for "video"), or an overlay scene. Generated video is NOT set here — it's the state a rendered still reaches through animate_segment (voice=true for a Talking Head), and a "video" target without media_source="real" is refused with that guidance. segment_type "image" with carry_frame=true reverts an animated shot back to its still for free. media_source="real" turns the shot into fetched media with no start frame and no generation. carry_frame=true reuses the already-rendered image instead of recreating it; ignored for a real target. SFX and overlays always survive a type change. dry_run=true previews what would be kept / staled / recreated / deleted before you commit.
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  • Animate a sprite through up to three fixed keyframes - initial_image, middle_image and final_image (each a URL or base64) - producing a spritesheet that interpolates through the provided frames in order. At least one of initial_image or middle_image is required (a final_image alone has nothing to anchor the animation); any keyframe may be omitted. The motion_prompt is optional here - when omitted, the motion is derived purely from the keyframes. Runs on the Forge family, the only models supporting middle keyframes: Forge (default) or Forge Pixel for pixel-art sprites; both share the same durations and pricing. The job result is a single sprite result directly (spritesheet URL, frame layout, and optionally a GIF or individual frame URLs when requested) with no separate polling step. Credits are charged only on success, based on the produced duration and never more than the duration you requested. Use animateSprite instead for the classic single-image + text-prompt animation with model choice. Pass an optional request_id to tag the result so you can locate it later via `GET /assets/sprites/results`. Requires an API key (user scope). Returns 202 with a job id immediately; poll `getApiJob` (pass `wait: 30`) until status is succeeded, then read its `result` field, which is exactly the response documented for this operation. Each account may have up to 50 generations queued or running at once; beyond that submissions return 429 (PENDING_JOBS_LIMIT) - wait for jobs to finish. Credits: cost varies by model and duration (credits/sec): Forge 1.5/s (min 4), Forge Pixel 1.5/s (min 4); see this endpoint's full pricing table in the API docs.
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  • PAID (0.01 USDC). Store a memory in your isolated bi-temporal namespace. Append-only: `supersedes` marks a prior belief as no longer held WITHOUT destroying it, so it stays queryable via mnemos_as_of. `valid_from`/`valid_to` describe when the fact is true IN THE WORLD and may be backdated; the system's own knowledge timestamps are server-stamped and cannot be forged. Returns an x402 quote; requires header X-TENANT-KEY once settled.
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  • Queue an asynchronous frame extraction - the tool to reach for when you need to SEE a video: fetches sourceUrl (or, with upload: true, waits for you to PUT the bytes to the returned uploadUrl) and extracts still frames as jpeg, webp or png. mode is REQUIRED and picks the sampling (all, every_nth, interval, keyframes, evenly_spaced, timestamps); there is no default because every candidate implies a rate you did not ask for. A finished job's resultUrl is a JSON MANIFEST: source display dimensions, fps, rotation, an echo of your parameters, frame_count, and one entry per frame with index, pts_time (seconds in the source) and its own download url on this gateway - fetch the manifest, then the frames you want. Up to 1000 frames per job; "all"/"interval" on a long source can exceed that and fail fast, so prefer interval, evenly_spaced or timestamps. Unreadable input, audio-only files and still images FAIL here (probe_media diagnoses those). Download within 24 hours. Paid: $0.03 USDC via x402 (base mainnet), or a frames-kind retryVoucher.
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  • Render a click-driving YOUTUBE / Shorts / Instagram THUMBNAIL or video cover — the full production pipeline (concept framework → casting → scene → render → surgical tweaks → text), not a bare image prompt. Use this for any "thumbnail", "video cover", "video preview" or MrBeast-style packaging ask INSTEAD of generate_image. About 9 credits per variant; the headline overlay is free. CONCEPT — every thumbnail must open an INFORMATION GAP (the image raises a question the title answers) while staying truthful to the video. Brainstorm ≥5 concepts across the 16 frameworks before you pick, and feel free to combine two. Frameworks (pass as `framework`): before_after · social_ui · three_step · screenshot · posed_portrait (the default) · posed_action · specific_day · graphical · landscape · map_aerial · product · adding_text · repetition · size_difference · news_clip · amplified_reality. Call hermoso_capabilities for each one's full 'realize it with' note plus the emotion, overlay-style, font and rim-colour catalogs. THREE GATES, all BEFORE you render: 1. WHO IS IN FRAME — never assume and never silently substitute a stranger. If the framework puts a person in frame and no face photo is attached, the tool refuses (nothing rendered, nothing charged) and tells you to ask the user once: themselves (send a face photo → the identity gets locked), a generated person (`castGenericPerson:true`), or a people-free framework. 2. TEXT — the default is a CLEAN render with the headline TYPESET OVER THE TOP afterwards (free, always legible, correctly spelled). Just pass `headline`. Only set `bakeText:true` if the user explicitly asks for the words painted INTO the image — verified live, that renders the asked-for words correctly but leaks garbled invented text across the rest of the frame. Never infer text intent from the topic or the framework. 3. HOW MANY — ask once whether they want one thumbnail or a SET (offer 4: the same concept at different emotions and/or camera takes). Default is 1; `variants` caps at 16. IDENTITY LOCK is automatic for every attached face photo. `emotion` is the single biggest CTR lever on a face: shock · hype · fear · confusion · determination · smug · charisma · disgust · awe · rage · laugh (or your own phrase). Finished thumbnail needs a fix? Re-call with `tweak` + `sourceImage` for a surgical, pixel-faithful edit (emotion / background / background_color / rim_light) instead of re-rendering — tweaks chain. ALWAYS check the returned postRenderCheck against the image before you present it. PROMPT LANGUAGE — write every DESCRIPTIVE field in ENGLISH (`sceneBrief`, `keyElements`, `location`, `composition`, `background`, `topic`, each person's `describe`, and every `reference` field), translating the user's wording where needed: the image models are trained on English and a non-English scene description renders noticeably worse. Text that gets BAKED OR TYPESET stays verbatim in the user's own language — `headline`, `headlineLines` and `bakedUiText` are never translated.
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  • Core dossier check: Fetch https://<domain>/ and return all HTTP response headers, with an audit highlighting missing or misconfigured security headers. Use to review CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Referrer-Policy, and Permissions-Policy; for redirect tracing use dossier_redirects instead. Single GET via fetch, 5 s timeout, captures raw response headers before any redirect is followed. Returns a CheckResult: on success, {status:"ok", headers:{...}, securityAudit:[{header, present, value},...]}; on failure, {status:"error", reason}.
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