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469,988 tools. Updated 2026-08-21 09:48

"3D content, models, or technology" matching MCP tools:

  • List skills available in the Heista skill library. Returns name, description, domain (shared / image / video / research / strategy / copy / creative / generation), type (foundation / registers / models / methodologies), version, and source_folder (managed-agents / chat-agent). Returns frontmatter only — no body content (use load_skill for that). Filter by domain, type, or source_folder. Use BEFORE load_skill to discover what craft knowledge is available without paying the body-read cost. Free, read-only.
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  • Long-range climate projections from bias-corrected daily CMIP6 models, covering 1950-01-01 to 2050-12-31 at any coordinate. Answers "what will conditions look like through 2050?" — the future-projection counterpart to openmeteo_get_historical (ERA5, what happened). Daily resolution only. Available models: CMCC_CM2_VHR4, FGOALS_f3_H, HiRAM_SIT_HR, MRI_AGCM3_2_S, EC_Earth3P_HR, MPI_ESM1_2_XR, NICAM16_8S. A model name outside that list is sent upstream rather than rejected here, so a model Open-Meteo adds later still works; if upstream rejects the request, the error names the offending model on its own rather than the whole requested list. With 2+ models each variable appears once per model with the model name as suffix (e.g. temperature_2m_max_CMCC_CM2_VHR4); a single or omitted model returns plain variable names. Not all models carry all variables — missing combinations return null. Multi-decade daily pulls across several models produce thousands of records and spill to DataCanvas for SQL querying when canvas is enabled, returning a bounded preview with truncated: true when it is not.
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  • Returns the Picsart AI model catalog as plain data — renders NO widget or UI. Use this when YOU (the assistant) need catalog knowledge for your own reasoning: picking a model before `picsart_generate`, answering "which models support X", or comparing options — without pushing a model-picker widget into the conversation. When the user wants to SEE or browse models visually, use `picsart_list_models` instead (it renders the Picsart Studio picker). Same filters and result shape as `picsart_list_models`, but every item is rich by default: `id`, `name`, `mode`, `inputType`, `provider`, `badges`, `description`, plus `supportedAspectRatios`/`supportedResolutions` when the model declares an enum for that param — enough to answer "which models support 16:9" without `picsart_model_params`. 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`). 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), `concise` (default false; when true items carry only id/name/mode/inputType plus the ratio/resolution fields, to save tokens). 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: "audio", inputType: "music" }` returns music-generation 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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  • List all AI models available on Gonka Network with live pricing. Models work as drop-in replacements for OpenAI and Anthropic — same SDK, same API calls. Use this when user asks which model to use or wants alternatives to GPT-4o / Claude. Returns: model IDs (use directly in openai.chat.completions.create), status, USD per 1M tokens. After this: call calculate_savings() to see annual savings with these models.
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  • Ingest a 3D model from a public URL into APS OSS and kick off a Model Derivative translation job, returning the URN plus a browser viewer link and QR code. Supports 50+ formats: Revit (.rvt/.rfa), Navisworks (.nwd/.nwc), IFC, FBX, OBJ, SolidWorks, point clouds (E57/LAS/RCP), CAD (DWG/STEP/IGES), etc. When to use: you have a publicly downloadable 3D file (S3 presigned URL, GitHub raw, etc.) and need it translated to SVF2 so it can be viewed, measured, or clash-checked via other tools. When NOT to use: the file is only on a local disk or behind auth (fetch will fail) — first push it to a public URL. Do not call to re-translate a model already uploaded; call get_model_metadata instead. APS scopes: data:read data:write data:create bucket:read bucket:create viewables:read Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; OSS uploads size-limited per file to 100MB for direct upload, larger via resumable. Errors: 401 APS token expired/invalid — refresh; 403 scope or resource permission denied; 404 source file_url not reachable or bucket not found — check the ID; 409 bucket name conflict (bucket already owned by another app — pick a unique bucketKey); 429 rate limited — backoff and retry; 5xx APS upstream outage — retry with jitter. Side effects: NON-IDEMPOTENT. Creates the scanbim-models bucket if absent, uploads a new OSS object with a timestamped key (each call creates a distinct object even for the same input), submits a Model Derivative job (x-ads-force=true overwrites prior derivatives for the same URN), and inserts a row into D1 usage_log + models table.
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  • Detect website technology stack: CMS, frameworks, CDN, analytics tools, web servers, languages (via HTTP headers + HTML analysis). Use for passive reconnaissance; for full audit use audit_domain. Free: 30/hr, Pro: 500/hr. Returns {technologies: [{name, category, confidence%, version}]}.
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Matching MCP Servers

  • A
    license
    A
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    Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.
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    666
    MIT
  • A
    license
    C
    quality
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    maintenance
    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.
    17
    Apache 2.0

Matching MCP Connectors

  • 55 Concordance-tested financial models with published specs; responses cite assumptions and sources.

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

  • Get canonical FINN URLs for a brand and its models — for building internal linking blocks on SEO pages. For each model returns three URLs that target DIFFERENT funnels: `mdp_url` (marketing/brand page), `plp_subscribe_url` (subscription product listing, /de-DE/subscribe/{brand}_{model}), and `plp_leasing_url` (leasing product listing, /de-DE/leasing/{brand}_{model}). Use `plp_leasing_url` when linking from a Leasing advisory, `plp_subscribe_url` when linking from subscription content. If `model` is omitted, returns all currently available models for the brand.
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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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  • List OECD dataflow refs we have pre-vetted, grouped by topic (gdp, labour, prices, finance, households, health, demographics, projections, tax, education, environment, technology). Pass the flow_ref to fetch_dataset. For everything else use search_dataflows or browse https://data-explorer.oecd.org.
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  • Inspect a public company domain and return structured identity, technology, social, contact, DNS, email-infrastructure, and AI-readiness evidence. Use `schemaforge` instead for a paste-ready JSON-LD template and remediation diff, or `deep_audit` when both outputs are required together. Public data only; this tool makes no site changes.
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  • One sector's drill-down: every member of the sector scored and ranked by opportunity, plus the sector's own ETF row. Accepts a sector name (e.g. 'Energy', 'Information Technology') or its ETF symbol (e.g. XLE, XLK). Unknown values return the sector directory. Free tier: one market day delayed. Live sibling (x402, pay-per-call): get_sector_read_live.
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  • List all AI models available through DPX Compute. All models are free-tier (no token cost) — routed via OpenRouter. Returns model IDs, provider, capability strengths, context window, and speed tier. Use this before compute.route to understand what models are available and pick the right one for a task. Free.
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  • Work out how a shipment fits into shipping containers, trucks or pallets, using a real 3D bin-packing solver. Describe the cargo in plain English -- quantities, dimensions, weights, and any constraints such as fragile, non-tiltable, max stack height or a preferred container type -- and get back which containers are needed, how full each one is, anything that did not fit, and a link to an interactive 3D load plan. Use this instead of estimating from volume. Volume arithmetic ignores stacking rules, orientation and weight limits, and overstates what fits by a wide margin on real cargo.
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  • Convert a single source image into a textured 3D model (image-to-3D). Synchronous: the call blocks while the mesh is generated, decompressed, and re-uploaded, then returns a downloadable GLB model_url plus an array of snapshot image URLs rendered from different angles (handy for previews). Accepts optional mesh controls: target_num_faces (max triangle count, 1000-200000, default 50000), texture_size (1024 or 2048, default 2048), and texture_type ("pbr", "simple", or "none", default "pbr"). Credits are charged only on success. Pass an optional request_id to tag the result so you can locate it later via get3DModelResults. Requires an API key (user scope). Credits: This endpoint consumes 3 credits per call.
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  • List saved viewpoints / camera positions and top-level view containers for a translated Navisworks model. Pulls the metadata view list and enriches each 3D view with its first two levels of the object tree (viewpoint folders typically live there in NWD files). When to use: when preparing a coordination meeting and you need a quick index of every saved viewpoint (e.g. "Level 3 Mech Room", "Clash - duct vs beam gridline C-4") to drive screenshots or BCF-style issues; when an agent needs to deep-link a 2D sheet or 3D camera into the APS Viewer. When NOT to use: does not return camera matrices (position/target/up vectors) — APS Model Derivative does not expose those from the NWD viewpoint XML; for full camera data the source NWD must be opened in Navisworks Manage. APS scopes required: viewables:read data:read. Rate limits: APS default ~50 req/min; this tool fans out one object-tree call per 3D view (capped implicitly by metadata view count, usually <5). For federated models with many sheets this can approach the per-minute quota — cache the result. Errors: 401 token (retry); 403 scope (report); 404 URN not found / translation incomplete; 409 N/A; 422 model returned empty metadata (returns viewpoint_count:0 rather than throwing — agent should verify translation via nwd_export_report); 429 rate limit (backoff); 5xx APS upstream (retry once). Per-view object-tree failures are swallowed so the overall call still returns the metadata-level view list. Side effects: none. Pure read. Idempotent. Logs usage to D1 usage_log. Results are capped at 100 viewpoint entries.
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  • Returns one or more Agrus case studies (NDA-protected; customer names are kept private, codenames + technology + outcomes are open). Filter by slug or vertical, or call with no args to list all. Use this for proof of prior work.
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  • Search V³ News for tracked geopolitical events. Use when the user asks what is happening on a topic, in a country, or in a domain (e.g. security, energy, finance, technology). Returns a ranked list of events with why-it-matters, risk/impact/signal scores, and a v3.news link for each. Args: query: free-text topic (e.g. "Iran sanctions", "Taiwan"). Optional. country: ISO-3166 alpha-2 code to filter by (e.g. "US", "CN"). Optional. category: V³ category slug — one of geopolitics, security_risk, energy_resources, finance, markets, macroeconomics, public_finance, trade_supply, technology, science_biosecurity, environment_climate, business. Optional. limit: max results, 1-20 (default 10).
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  • List the URBot catalog of 150+ trained vertical AI expert bots with slug, name, tagline, category, and price tiers (most bots start at $1). Optionally filter by category (e.g. education, health, finance, legal, technology, outdoor, 3d-modeling, game-dev, 3d-printing, media). Use the returned slug with get_bot, chat_with_bot, or get_skill. URBot bots keep your data yours - each one is downloadable and runs locally.
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  • Given a deprecated or retiring model, return the provider's recommended replacement(s) and, when none is published, active models from the same provider to consider.
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  • List available models and their prices — free, no payment, no authentication required. Read-only: no state changes; data is served from the server's local config, so repeated calls return identical results (idempotent). Accepts no parameters: the input schema is an empty object, and any arguments passed are ignored. Calling it without arguments returns the complete catalog with per-token prices; there is no filtering, pagination, or configuration. Use this tool to inspect models and prices before calling the paid chat_completions tool. Same data as GET /v1/models (§5.2). Do not use it to generate text (use chat_completions) or to estimate a specific request's cost (use get_price_estimate).
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