"Computer Aided Design" matching MCP tools:

• designesy_readiness_scoreA

  DesignesyA

  Score a URL for design-system AI readiness — the 6th maturity axis (zeroheight 2026). 10 checks probe the target origin for machine-readable artifacts: DTCG token files, llms.txt, agent.json, MCP endpoint (tools/list), DESIGN.md, token $description, component schemas, sitemap.xml, robots.txt, and Open Graph/Twitter meta. Use this to verify whether a design system is the default context AI tools build from, or whether AI is silently working around it. When NOT to use: for full design-contract scoring, use designesy_score; for AI-drift detection, use designesy_drift_score. Executable — fetches the URL and probes the origin via HEAD/GET for each artifact. No browser needed. Returns JSON: { ok, url, score (0-100), grade (A-F), pass, warn, fail, total, checks[{id, item, category, status, detail}] }. Results cached ~24h per URL.

  ConnectorNo auth

• read_schematicA

  boardrepoA

  Use when the user asks how a public board is wired, what a component (e.g. U1) connects to, or which pins are on a net (e.g. GND), in that design. Returns the board's latest geometry-free connectivity. No focus returns a bounded overview (components + a net index); ref returns one component and the nets it connects to with the other pins on those nets; net returns the pins on that net. These are in-design connections, not an authoritative manufacturer pinout, and a very large design may be truncated (the response flags this). Prefer a focused ref or net over repeated overviews. Use get_bom for purchasing and read_file for raw source. If nets are still computing, continue with the components shown and try again shortly rather than inferring connectivity.

  ConnectorOAuth

• designesy_design_reviewA

  DesignesyA

  Get the Designesy Design Review framework — an 8-dimension rubric (Purpose, Clarity, Context, Inclusion, System coherence, Durability, Delight, Responsibility) plus the agent prompt, output format, and verification checklist for a qualitative design critique. Use this when you want a structured rubric to critique a design holistically, rather than a numeric compliance score. When NOT to use: for a deterministic numeric score, use designesy_score; this tool gives you a rubric, not a number. Read-only — returns the rubric + prompt. The calling agent performs the actual critique (this tool does not evaluate the design for you). Returns JSON: { rubric, dimensions[8], agent_prompt, output_format, verification_checklist }. Pass artifact/purpose/context/rules to get a pre-filled critique prompt; omit all four to get the blank framework.

  ConnectorNo auth

• designesy_compareA

  DesignesyA

  Diff two design systems from live URLs — the only URL-scoped design-token diff engine. Fetches both URLs in parallel, extracts their :root custom properties, and produces a structured diff across 8 dimensions: tokens added (in A not B), removed (in B not A), renamed (heuristic Levenshtein ≤ 2), value-changed (same name, different value), scale-stop-changed (spacing/radius/color scale steps), contrast-drift-per-pair (WCAG contrast ratio change for shared color tokens), structure-delta (token count + category distribution), and score-delta (runs /score on both URLs and diffs). Use this to answer "what actually changed between two design systems" or "how does our design system differ from a reference". When NOT to use: for single-site drift detection, use designesy_drift_score; for continuous monitoring, use designesy_monitor_score. Executable — fetches both URLs, extracts CSS + tokens, computes diff. No browser needed. Returns JSON: { ok, urlA, urlB, score (0-100, diff completeness), grade, pass, warn, fail, total, tokensA, tokensB, added[], removed[], renamed[], valueChanged[], scaleDiff, structureDelta, contrastDrift[], scoreDelta, checks[] }. Results cached ~24h per URL pair.

  ConnectorNo auth

• get_quantum_exposureA

  mcpA

  Call this when the user asks how much Bitcoin is vulnerable to a quantum computer, about quantum-exposed supply, P2PK coins, or Satoshi-era exposure. Returns the latest daily measurement from ByKaranteli's own Bitcoin Core node: exposed BTC and its share of held value and UTXO count, composition by script family, dormancy cohorts, the dormant-P2PK watch set, and provenance hashes (base_height, base_hash, txoutset_hash) so any figure can be re-verified against any node.

  ConnectorNo auth

• roastify_generate_artworkA

  roastify-mcpB

  Generate packaging artwork from one of your saved Design Studio designs. This personalizes a template you already authored: it rewrites that design's named text and image placeholders. It cannot author a design from scratch, and the artwork it produces is NOT attached to a product — Roastify's API has no product-create or storefront-sync surface. You get an artwork URL and carry it onward yourself. Roastify renders asynchronously, so this returns a job id straight away. Check it with roastify_artwork_status, which is free.

  ConnectorNo auth

• get_design_historyA

  MozaikaA

  Measured design CHANGE HISTORY for a live-decoded domain — the Decode Ledger. Token-level diffs between deep decodes over time: "radius 4px→8px", "primary hover #4032C8→#0A2540", "motion dominant 150ms→200ms", each dated. Use it to see how a product's design system is EVOLVING (no screenshot library can backfill this). site = a domain ("stripe.com") or product name. Returns first/last decode dates, decode_count and the dated change entries; empty history = measured, stable so far.

  ConnectorNo auth

• ateam_design_advisorA

  ateam-mcpA

  CONSULT THIS DURING DESIGN — before and while you design a skill/solution. Describe what you're building; it returns POINTERS to the platform capabilities that fit (per-actor storage, widgets, triggers, sub-agents, mobile data, run-scripts, multi-skill, GitHub, …), each with the /spec topic to read next (via ateam_get_spec) and the tool to wire it. Also returns 'missing' hints (capabilities your goal implies but the design hasn't wired) and lifecycle hints (e.g. connect GitHub when the project will iterate). ADVISORY ONLY — you decide and own the design. Stateless: pass the current design_state each call; consult it as often as you like as the design evolves. If the reply carries `truncated: true`, the answer ran past the length budget and was CUT OFF: what is there is correct, but a capability's ABSENCE proves nothing — ask again with a narrower goal, or use ateam_spec_search, before concluding the platform lacks something.

  ConnectorNo auth

• principles.searchA

  AI Design Blueprint DoctrineA

  Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.

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• get_incidentsA

  commutescoutA

  Live CHP traffic incidents statewide, optionally filtered. Data: the California Highway Patrol statewide computer-aided dispatch feed - collisions, traffic hazards, disabled vehicles, closures as CHP logs them. Refreshes about once a minute; incidents disappear when CHP closes the log. Fetched live on every call. Filters (combinable): - highway: a route like "I-80", "US 50", "17", "Hwy 99". Matches incidents whose location text mentions that route. - center: "lat,lon" with radius_km - incidents within that circle. THIS IS THE RIGHT FILTER FOR A TOWN OR PLACE NAME: use your knowledge of where the place is (e.g. Coyote, CA -> "37.22,-121.74") with radius_km 15-30. A circle catches every road around the place, not just one highway. - area: substring match on the CHP dispatch-area name. These are CHP communication-center names ("Hollister Gilroy", "East Sac", "Golden Gate"), NOT town names - do not pass a town here. There is no county filter because CHP's feed carries no county field; for a county, use center on the county seat with a radius covering the county. Limits: locations are free-text from dispatchers; a few incidents lack usable coordinates and are omitted. No history - current logs only.

  ConnectorNo auth

• principles.searchA

  AI Design BlueprintA

  Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.

  ConnectorNo auth

• set_design_overviewA

  Forge EngineA

  Write the Design Document's Overview — the human-readable page a new team member reads first. WRITES DIRECTLY (no Inbox): it is a derived, clearly-labelled AI summary, not design truth, and the owner can clear or rewrite it in one click. HARD RULES, same as the in-app button: use ONLY facts stated in the design (call get_design_document with for_summary:true first); invent no mechanics, numbers or names; describe, never evaluate; write in the design's dominant language. Structure: `### What this is` · `### The core loop` · `### How the systems fit` (which system feeds which — the part a raw spec list cannot give) · `### Edges` (ONLY if the design states scope limits / open questions). 250-400 words, no top-level heading. Forge stamps the project version it was compiled from, so the owner is told when the design has moved past it.

  ConnectorNo auth

• designesy_contractA

  DesignesyA

  Get the Designesy design-system contract — the canonical tokens, motion, acoustic, takt, cadence, typography, components, and verification rules that define what the Designesy org considers legitimate design. Use this when you need the actual contract values (token names and values, motion timings, accessibility rules) to author, check, or bind a design. When NOT to use: for a pass/fail score of a live site, use designesy_score; for an agent-skill-format export, use designesy_skill_md. Read-only — cached ~24h server-side. Returns the full contract JSON, or a single section when "section" is provided. Pass section to get one slice (e.g. "motion" for just the motion tokens) instead of the full contract — saves tokens when you only need one dimension.

  ConnectorNo auth

• list_design_changesA

  MozaikaA

  What actually changed in the web's design systems lately — the nightly Drift Ledger feed. Mozaika re-measures ~100 of the most-referenced products every night and records a dated row per product even when nothing moved, so this is a real time series, not a guess: how many products held every token, which ones shipped a change that stuck (with before/after values and the date), and which design tokens move most often across the web. Use it to answer "does anyone actually redesign?", to ground a claim about design churn with a citable measurement, or to spot that a reference you rely on has moved. For one product, call get_design_drift(domain). Args: limit: how many confirmed changes to return (1-40, default 10). Free.

  ConnectorNo auth

• request_file_uploadA

  Extend MCPA

  Create an upload link for the user to add files from their computer (files group). Returns a dashboard URL; the user uploads in their browser and the files land in the target workspace. Call this last in your turn: write the returned link in your reply, then END THE TURN — do not call get_file_upload or any other tool until the user says they are done uploading. Follow any llmContext guidance included in results.

  ConnectorOAuth

• get_fabrication_quoteA

  Agentic Fabrication Network (AFN)A

  Get ranked, purchasable offers (price, ETA, preview image) for fabricating a physical item from a design file. process=fdm_print for 3D printing a model (STL/OBJ/PLY/3MF/AMF/STEP/IGES), process=cnc or process=sheetmetal for machined/bent metal parts (STEP, IGES, DXF), process=decal for stickers/decals from artwork (any common image or design file — PNG/JPG/HEIC/TIFF/GIF/BMP/WEBP/AVIF/SVG/PDF/AI/EPS/PSD/CDR, auto-converted). A .ufp file (UFP part container: the design plus saved spec/constraints in one) is accepted anywhere a design file is — its saved intent applies automatically and anything the user states now wins. If the user just drops a file and asks for a price, omit process — UFP routes it. Provide the design either as design_file (an image/file the user attached or you generated — preferred) or file_url (a public URL). REORDERS: if the user has a UFP part number (from a receipt email or a previous session, looks like UFP-… or part_…), pass it as part_number INSTEAD of any file — the stored design and spec are reused and re-shopped across all current vendors. Locked parts additionally require share_key (from the owner's share link). Returns offers across vendors like Google Flights returns flights.

  ConnectorNo auth

• create_graph_nodeA

  RationalBloksA

  Create a single node in a deployed graph project. REQUIRES: Project must be deployed (use deploy_graph_staging first). The entity_type must match an entity key from the project schema. Use get_graph_data_schema to see available entity types and their fields. Example: entity_type: "person" entity_id: "alan-turing-001" data: {"name": "Alan Turing", "birth_year": 1912, "field": "Computer Science"} The entity_id is your unique identifier — use meaningful IDs for knowledge graphs.

  ConnectorNo auth

• adcritter_get_design_guideA

  AdCritter for BuildersA

  Returns AdCritter design guidance for an entity at a caller-chosen guidance level - screen experiences, API integration patterns, and design philosophy. The default ('full') returns step-by-step prescription (exact layouts, colors, copy text, column orders). Request 'patterns' for balanced hints including common design patterns with softened vocabulary. Request 'facts' if you have strong visual-design instincts and just want API integration bindings (or call adcritter_get_api_reference and adcritter_get_usage_guide directly and skip this tool). Guidance is format-agnostic - it describes outcomes and integration, never prescribes frameworks or architecture. Available entities: ad, advertiser, audience, authentication, blueprint, campaign, geo, media-asset, plan, report, settings.

  ConnectorNo auth

• explore_design_conditionsA

  epwforge-mcpA

  Interactive single-site design-conditions explorer. Returns full ASHRAE design conditions + diurnal chart for the requested scenario. In MCP Apps-capable hosts (Claude Desktop, ChatGPT, VS Code, Goose), the response renders as a widget with sliders for SSP / year / percentile / UHI — dragging a slider re-calls this tool live. Use when a user wants to interactively tune a single site. For multi-site comparison, use analyze_weather(urls=[...]) instead. Defaults to present-day TMY (no morph) — pass ssp+year for future scenarios. P75 default percentile is design-realistic; P50 underestimates the tail. No auth required.

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• cloning_diagnoseA

  workbenchA

  Work out why a cloning experiment failed: no colonies, every clone empty vector, or no PCR band. Takes your design (method, parts, enzymes, primers, host methylation state) plus what you actually observed (colony counts on the plate and on each control, screening tally, band sizes, whether the ladder ran) and returns causes ranked by evidence — each with the deterministic fact from the design or the observation that implicates it, the cheapest observation that would separate it from the next candidate, and the next experiment. Causes the observations eliminate are reported as eliminated, naming the observation that did it; causes the design makes impossible are not listed. No probability is computed anywhere — the ordering is of evidence, not of likelihood, and `ranking.evidenceBased` says so when the inputs separate nothing.

  ConnectorNo auth

• crear_disenoA

  mueblitoA

  Crea una escena 3D con uno o varios muebles y devuelve un link editable directo al editor de Mueblito — el link /d/<code> abre el diseño listo para ver en 3D, mover piezas, ajustar medidas y generar presupuesto. Usala cuando el usuario quiere visualizar cómo quedarían los muebles en un espacio o compartir un diseño con un carpintero o cliente. Prerrequisito: si no sabés los ids de los presets, llamá primero a listar_presets. Cada mueble se especifica con preset o params; la posición y rotación son opcionales (si no se dan, los muebles se distribuyen en fila automáticamente). Limitación: el link es estático (no se guarda en servidor); no requiere cuenta. (create 3D design, furniture layout, shareable room design, Argentina interior design)

  ConnectorNo auth