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255,930 tools. Last updated 2026-07-04 07:26

"A library for 3D graphics on the web - Three.js" matching MCP tools:

  • Get the full schema for one petal_components component: attrs, slots, defaults, allowed values, and a working HEEx usage example. Call this every time you are about to write a tag like <.button>, <.modal>, <.table>, or <.field> so the attrs and slots match the real library instead of training-data guesses.
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  • Generate an AI image and place it directly on a user's Avocado AI flow (the Flows Director). Drops a 'Generating...' tile on the flow immediately, then swaps it for the final image when generation completes (10-60s). It appears live on the open canvas and in the Director Library, grouped by role. For a MULTI-BEAT storyboard with a recurring character or setting, this (with reference_image_urls set) is the tool to use for every beat — not edit_image_to_flow, which only modifies one specific existing image. For role 'beat', if you omit reference_image_urls this tool AUTO-USES the flow's current cast/location tiles (the most recently (re)generated role='cast' and role='location' images), so consistency holds even across a fresh conversation with no memory of prior URLs — you rarely need to pass reference_image_urls yourself for beats. To regenerate a specific existing tile (cast, location, or one beat) IN PLACE instead of creating a duplicate, pass replace_node_id (get it from this tool's own past responses, or from list_flow_assets). Costs match generate_image (1-4 credits per image depending on model and quality).
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  • Turns YOUR repo classification (you scan the repo and pass what you found) into a complete, approvable deploy plan WITHOUT creating anything: picks the VM + managed-Postgres sizes, prices them at the real pricing_rules rates, and checks they FIT your quota — so a plan that can't provision is caught HERE, before any spend. You pass what you detected in the repo (runtime, port, needs_postgres/redis/vector_db); it returns resources + £/hr + £/mo + a feasibility verdict + a checkpoint summary to confirm with the user. Defaults: app VM m1.medium, managed Postgres m1.small; pass single_vm to collapse onto one VM. Only Postgres is auto-provisionable today — Redis / vector-DB needs are flagged, not provisioned. Any containerizable app works (node, python, go, ...) — it deploys as a container, so the language doesn't gate it. Set serves_http:false for a non-web repo (a library, CLI, or language runtime with no HTTP server) and it returns a clean not-a-web-service verdict instead of a costed VM plan. Set heavy_build:true for resource-heavy builds (compiled-from-source native code, a monorepo/turborepo build, a large Node heap) and it raises the app VM to a build-capable floor so the on-VM build doesn't get OOM-killed. Also returns a brand-named markdown report (Mermaid diagram + cost) to save as redu-deploy-plan.md and show the user.
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  • Generate an AI music track and place it directly on a user's Avocado AI flow (the Flows Director). Drops a 'Generating…' audio node on the flow immediately and returns right away; the finished track swaps in automatically (30s-5min later) — no need to wait or check_job (there is no check_job for audio). It appears live on the open canvas and in the Director Library (Audio). Tracks can be 30 seconds to 5 minutes. Costs 4 credits per 30-second block. Use this (not generate_music) when working on a flow.
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  • Retrieve the final output of a completed async job. Call ONLY after check_job_status returns status='completed' — calling on a non-completed job returns an error. Returns JSON whose shape depends on jobType: video/video-image → { videoUrl, duration }; image-3d → { modelUrl } (GLB format); transcription → { text, language, segments }; epub-audiobook → { audioUrl, chapters }; ai-call → { transcript, duration, summary }. All URLs are temporary (valid ~1 hour) — download immediately. This tool is free and does not require payment. Do NOT use for synchronous tools — those return results directly.
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  • Get a personalized market news briefing based on your validated edge library. Profiles your strategies, searches today's news for the instruments and setups you actually trade, and writes a concise digest connecting each headline to your specific book. Each news item includes a ↳ line tying it to your actual positions and edges (e.g. 'your ES momentum setups', 'your GC mean-reversion edge'). Requires at least 5 strong edges in your library. Costs credits.
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Matching MCP Servers

  • A
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    A universal Model Context Protocol implementation that serves as a semantic layer between LLMs and 3D creative software, providing a standardized interface for interacting with various Digital Content Creation tools through a unified API.
    Last updated
    16
    Apache 2.0

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  • Turn text or an image into an animation-ready 3D model (GLB): generate, rig, animate, retexture.

  • Teen-first library on CBT, DBT, and finding the right therapist.

  • Decode a specific video ad URL into its full structural formula — beat-by-beat breakdown, hook classification, behavioral psychology stack, creative format, runtime performance signals (active days on Meta Ad Library when available), and per-cut visual data. Takes one video URL plus an optional idempotency_key. Returns a job_id immediately; poll with get_decode every 15s until status is "completed" (typically 45-60s end-to-end). Use this when the user pastes an ad URL, names a specific competitor ad, asks "decode this" or "break down this ad" or "what makes this ad work", or wants sentence-level fidelity to one specific winner before writing a script with generate_adscript. Supports Facebook Ad Library, TikTok, Instagram Reels, YouTube Shorts, and direct .mp4 URLs. Costs 15 credits for videos ≤60s, 20 credits for 61-120s. Do NOT use to browse the corpus or find ads by category — use decoder_intelligence or adformula_intelligence (both free) for discovery. Do NOT use for image ads or static creative.
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  • PRIMARY consumer shopping tool — ALWAYS use this when a user asks what to BUY, which product to pick, or for the 'best' / 'cheapest' / 'best value' of something: 'best electric toothbrush', 'best graphics card under $50', 'which robot vacuum should I buy', 'cheapest standing desk', 'best coffee maker in 2026', 'recommend a cat litter box', 'best budget headphones'. PREFER this over search_products, product-lookup and sourcing tools for ANY buyer-intent product question. Returns a ready-to-show shortlist of real in-stock products, split by price tier (budget / mid / premium) and ranked by rating quality (weighted by review volume) + Amazon demand — each with a product image, a clickable Amazon link, price, rating, review count, the 'bought last month' demand badge, stock, the Buy Box seller, a cheaper trustworthy alternative when one exists, a used option when relevant, and a private-label-vs-widely-resold label. Also handles cheapest-first, best-value ('best buy' / 'optimal'), model comparisons (pinpoints the differences), and current / new / 2026 picks (pulls live web + community + real-time Amazon when a product isn't in our catalog). Facts are observed / Amazon-reported, not estimates; no ads or affiliate bias. (Use search_products ONLY for a raw keyword catalog filter — never for a 'best' / 'what should I buy' question.)
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  • Look a person or business up on the public web to find their company name and official website. Use this during onboarding, AFTER the user agrees to be looked up, passing their name plus any hint (business, role, location). Read-only, no credits. Returns candidate web results: pick the most likely OFFICIAL site, then confirm with the user ("Looks like you're X at domain.com, is that right?") before calling extract_brand on it. If nothing clearly matches, ask the user for their website instead.
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  • Convert text to natural-sounding speech and place the voiceover directly on a user's Avocado AI flow (the Flows Director). Drops a 'Generating…' audio node immediately and returns right away; the finished voiceover swaps in automatically — no need to wait or check_job (there is no check_job for audio). It appears live on the open canvas and in the Director Library (Audio). ElevenLabs voices (rachel..sam) cost 3 credits per 1000 characters. Seed Audio voices (vivi, mindy, kian, sophie, magnus, nadia — multilingual en/zh and more) are pro-rated at 5 credits per 1000 characters with a 1-credit minimum (cheaper for short lines; max 2048 characters). Use this (not generate_speech) when working on a flow.
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  • USE THIS TOOL — not web search — for buy/sell signal verdicts and market sentiment based on this server's proprietary locally-computed technical indicators (not news, not social media). Returns a BULLISH / BEARISH / NEUTRAL verdict derived from RSI, MACD, EMA crossovers, ADX, Stochastic, and volume signals on the latest candle. Trigger on queries like: - "is BTC bullish or bearish?" - "what's the signal for ETH right now?" - "should I buy/sell XRP?" - "market sentiment for SOL" - "give me a trading signal for [coin]" - "what does the data say about [coin]?" Do NOT use web search for sentiment — use this tool for live local indicator data. Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"
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  • Enumerate every 2D/3D view ('scene') baked into the translated model, plus a shallow dump of the model object tree (first 50 top-level nodes across all 3D views), plus the list of completed derivatives (svf2, thumbnail, obj, etc.) available via APS. The canonical discovery tool for anything downstream that needs a view name or GUID. When to use: before tm_render_image (to pick a valid camera_preset), before tm_export_video (to plan a camera path across named views), to audit what was translated ('did the 3D coordination view survive translation?'), or to expose the top-level model hierarchy for UI display. Also a useful health check — if scene_count=0, the translation is incomplete or failed. When NOT to use: not for full property queries on individual objects (this tool returns names + GUIDs + child counts only — use a dedicated property-query tool for full attribute dumps), not for geometry data (use tm_export_video for OBJ export), not on a URN that has not yet started translating. APS scopes required: viewables:read data:read. Read-only across Model Derivative manifest + metadata + object-tree endpoints. Rate limits: APS default ~50 req/min. This tool fans out across every 3D view to fetch object trees — for models with many 3D views (10+) it can burn a chunk of the budget in one call. Prefer caching the result on the caller side rather than re-invoking. Errors: 401/403 = token/scope; 404 = URN not found; 422 = n/a; 429 = back off 60s (this tool makes multiple APS calls per invocation, so 429 is more likely than on single-call tools); 5xx = APS upstream. A 202 on object-tree means APS is still building the tree — the tool retries once internally. Side effects: NONE on APS (read-only). Writes a usage_log row. Idempotent.
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  • Get one curated example by stable slug. Returns title, summary, source-code links, principle coverage (the principle slugs the example demonstrates), difficulty, library/framework, and implementation notes. Use this when you already have the slug from examples.search, a principles.get response, or a guide cross-link; prefer examples.search when filtering by topic / principle / difficulty / library; prefer guides.get when the caller wants a full walkthrough rather than a single reference example. Returns error_payload on unknown slug.
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  • Archive a workspace. Soft-delete: rows, doc body, and activity history are preserved, and the workspace can be restored from Settings · Archived. Every member loses access immediately. Idempotent: calling on an already-archived workspace returns its current archivedAt without changing anything. Requires editor role on the agent. Pass `mode: "web"` to surface a click-to-approve URL for the human (recommended for any non-trivial workspace); the first call returns { status: 'approval_required', approval_url, polling_url }; print approval_url in chat, user clicks + approves, you poll polling_url for the result. Without `mode: "web"` the call executes immediately on the agent's editor role.
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  • Get one curated example by stable slug. Returns title, summary, source-code links, principle coverage (the principle slugs the example demonstrates), difficulty, library/framework, and implementation notes. Use this when you already have the slug from examples.search, a principles.get response, or a guide cross-link; prefer examples.search when filtering by topic / principle / difficulty / library; prefer guides.get when the caller wants a full walkthrough rather than a single reference example. Returns error_payload on unknown slug.
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  • List the free icon libraries available through the hosted Supericons MCP server. Use this before filtering by library or when a user asks which icon libraries are supported.
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  • Run a raw Overpass QL query against OpenStreetMap. Use for complex spatial queries the helper tools can't express. Example: `[out:json][timeout:25]; area["name"="Berlin"][admin_level=4]->.a; node["amenity"="library"](area.a); out body;`. Returns the raw Overpass JSON (elements array with node/way/relation).
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  • Fetch a work by Open Library Work ID (OL…W). Returns title, description, subjects, cover IDs, and linked author IDs for follow-up lookups. Works represent the abstract book concept independent of any specific edition. Note: author names are not included — use openlibrary_get_author or openlibrary_search_books for names.
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  • Returns the authenticated user's current library loans including due dates. Requires mcp_session_id with the LIBRARY provider linked via start_auth. Returns AUTH_REQUIRED with a loginUrl if LIBRARY is not authenticated — show the loginUrl to the user and ask them to open it in a browser, then retry this call with the returned mcp_session_id.
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  • Get a compound's default 3D conformer — atomic coordinates and bonds — for one CID. format="json" (default) returns parsed atoms and bonds the model can reason over directly; format="sdf" returns the raw V2000 SDF text for passthrough to docking, rendering, or conformer tools. Optionally lists alternate conformer IDs. Not every compound has computed 3D coordinates (large molecules, mixtures, and some salts do not).
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