Skip to main content
Glama
650,830 tools. Updated 2026-10-14 18:50

"A guide to UX/UI Design principles and resources" matching MCP tools:

  • Evaluate a design description against UX principles. Returns relevant principles, potential violations, and improvement suggestions. Screenshot pixel-diff is disabled on the hosted (remote) endpoint (unbounded image decode). Omit 'before_screenshot'/'after_screenshot' and pass a 'description' to evaluate the design against UX principles statelessly.
    ConnectorNo auth
  • Get design principles relevant to a UI context. Returns usability heuristics, laws of UX, Gestalt principles, accessibility requirements, typography rules, and color theory — matched to what you're designing.
    ConnectorNo auth
  • Search across all design principles, UI patterns, and business strategies. Use when you need to find specific guidance or don't know which category to look in.
    ConnectorNo auth
  • Download the Game Dev skill pack ZIP: game design, game feel/UX, level design, game programming, XR design and game audio skills with example prompts, quick-start guide and licence. Price: 39000000 atomic USDC. Payment authorization required before paid execution.
    ConnectorNo auth
  • Pro-tier. Fetch two web pages (your URL and a competitor's) and audit both against the Proximens GEO Engine principles using the same audit engine as audit_url, then compute the delta. INPUT: self_url and competitor_url (both required, http/https). RETURNS: JSON with a 0-100 score per URL (same scoring as audit_url), the principles each page satisfies, the principles each page VIOLATES that the other satisfies (delta_principles), and strategic insights on where to close the gap. USE WHEN you want a competitive GEO gap analysis between your page and a rival's.
    ConnectorNo auth
  • 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`.
    ConnectorNo auth

Matching MCP Servers

Matching MCP Connectors

  • A design harness for AI coding agents: design systems, design principles, icons and UI review.

  • Mlola UI components, tokens and design rules for coding agents, with a markup checker

  • Evaluate an array of content items (headings, prose, CTAs, labels, captions, metrics, outcomes) against UX-writing principles and deterministic heuristics. Returns a per-item verdict (pass/warn/fail) with matched principle ids, concrete issues grounded in principle text, a before→after rewrite suggestion, and an aggregate summary. Heuristics: metric items must carry a number+unit; cta/label must be action-led and ≤4 words; prose flags passive voice, jargon, and hedging; headings flag filler openers and buzzwords; captions flag duplication of any heading in the batch. Pure offline — no network or browser. Use this instead of evaluate_design when you need per-item content verdicts rather than the principle library.
    ConnectorNo auth
  • Fast design and accessibility check of UI code (React, Vue, Svelte, HTML, CSS, SwiftUI). Returns the top issues with severity, category and file:line in about 10 seconds. Call it when the user pastes or uploads UI code, asks whether a design is good or accessible, or when you just wrote or changed a component, page or view. You do not need to ask first. Pass each file with its real path, or for pasted code a path that fits it (pasted/Card.tsx, pasted/index.html) and the full code. Five quick checks cost one review credit (two on the free plan). It reads code only, not screenshots or URLs. It returns no score and no patch: fix the issues yourself. For a score or patches, use review_files.
    ConnectorNo auth
  • Fast design and accessibility check of UI code (React, Vue, Svelte, HTML, CSS, SwiftUI). Returns the top issues with severity, category and file:line in about 10 seconds. Call it when the user pastes or uploads UI code, asks whether a design is good or accessible, or when you just wrote or changed a component, page or view. You do not need to ask first. Pass each file with its real path, or for pasted code a path that fits it (pasted/Card.tsx, pasted/index.html) and the full code. Five quick checks cost one review credit (two on the free plan). It reads code only, not screenshots or URLs. It returns no score and no patch: fix the issues yourself. For a score or patches, use review_files.
    ConnectorNo auth
  • Gets the status and result of a design generation job started by create-design. Pass the job_id and continuation_token from the previous create-design or get-async-job response. While the job is still running, wait the number of seconds the response's polling_policy.wait_seconds gives, then poll again with the same job_id and the updated continuation_token. Never poll sooner than that: it returns the same answer and the design arrives no earlier. Follow the polling_policy.instructions in every response, and relay them to the user while they wait. When the job completes, share the design link with them. When the completed response carries design.print.is_printable as true, and you are replying in text alone — no UI surface of your own rendering the design — then alongside the design link tell the user they can also order this design as a physical print with Canva Print and share design.print.print_url. Otherwise say nothing about printing: when print is absent or is_printable is false, there is nothing to do and nothing to relay. Never tell the user a design cannot be printed.
    ConnectorOAuth
  • Gets the status and result of a design generation job started by create-design. Pass the job_id and continuation_token from the previous create-design or get-async-job response. While the job is still running, wait the number of seconds the response's polling_policy.wait_seconds gives, then poll again with the same job_id and the updated continuation_token. Never poll sooner than that: it returns the same answer and the design arrives no earlier. Follow the polling_policy.instructions in every response, and relay them to the user while they wait. When the job completes, share the design link with them. When the completed response carries design.print.is_printable as true, and you are replying in text alone — no UI surface of your own rendering the design — then alongside the design link tell the user they can also order this design as a physical print with Canva Print and share design.print.print_url. Otherwise say nothing about printing: when print is absent or is_printable is false, there is nothing to do and nothing to relay. Never tell the user a design cannot be printed.
    ConnectorOAuth
  • List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8 experience-design laws (the design.validate rubric); 'spec' = the 8 spec-quality laws (the spec.validate rubric). Use this when you need the full inventory or want every entry in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exact slug and need full detail.
    ConnectorNo auth
  • Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id, title, cluster, definition, rationale, implications, and risk-if-violated (laws also carry their eponym and validator_questions). Use this when you already have the exact slug from principles.list; prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster. Returns error_payload on unknown slug for the lens.
    ConnectorNo auth
  • Authenticated: returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest the user record concrete evidence. WHEN TO CALL: when the user asks 'what should I work on next' or 'what's weak in my Blueprint progress'; before suggesting which guide/example to consult. Pair with me.add_evidence to close gaps. WHEN NOT TO CALL: to lecture the user on principles they have already satisfied; on every conversation turn (state changes only when evidence is added). BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan). Returns thin_stages list with stage slug, course slug, missing principles, evidence_count, and a coaching_note.
    ConnectorNo auth
  • List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8 experience-design laws (the design.validate rubric); 'spec' = the 8 spec-quality laws (the spec.validate rubric). Use this when you need the full inventory or want every entry in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exact slug and need full detail.
    ConnectorNo auth
  • Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id, title, cluster, definition, rationale, implications, and risk-if-violated (laws also carry their eponym and validator_questions). Use this when you already have the exact slug from principles.list; prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster. Returns error_payload on unknown slug for the lens.
    ConnectorNo auth
  • Authenticated: returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest the user record concrete evidence. WHEN TO CALL: when the user asks 'what should I work on next' or 'what's weak in my Blueprint progress'; before suggesting which guide/example to consult. Pair with me.add_evidence to close gaps. WHEN NOT TO CALL: to lecture the user on principles they have already satisfied; on every conversation turn (state changes only when evidence is added). BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan). Returns thin_stages list with stage slug, course slug, missing principles, evidence_count, and a coaching_note.
    ConnectorNo auth
  • Plain-English explanation of how scoring works, the two governing principles, what is deliberately left out (protected characteristics, luck), and the privacy stance. Use to answer "how does this work / is this fair" questions.
    ConnectorNo auth
  • Return a canonical Clipkit doc as text. topic "card" = the ~8KB compact authoring card — the recommended context for authoring; "pattern-lighting" = the shine/neon/glow technique rigs; "pattern-data-viz" / "pattern-cinematic-ui" / "pattern-ui-screencast" / "pattern-promo-teaser" = ~4-5KB pattern cards (proven idioms: count-ups and bar rows; product hero shots with camera rigs; faked app UI with typing/cursor/clicks) — load ONE alongside the card when the brief matches its archetype; "agents" = the full authoring guide (fetch only when the card doesn't cover a need); "protocol" = the formal field spec; "brand" = brand reference. (Same docs offered as MCP resources, exposed as a tool so you can read them directly — resources are not always model-readable.)
    ConnectorNo auth
  • UI/UX guidelines and a review of a page against them. mode="guidelines" returns the principles — Nielsen's 10 heuristics, Hick's and Fitts's laws, WCAG 2.2, neurodiversity-inclusive design, motion and microinteractions (including when Lottie or Rive are worth their bundle cost), SVG craft and animation, light-first theming, lightness and responsiveness — optionally filtered by topic. Read them BEFORE designing or building UI. mode="review" statically reviews supplied HTML and CSS, or a URL, and reports what violates which principle. The review reads source and does not render it, so it cannot measure computed contrast, real target sizes, or where focus lands — it catches what is visible in the markup, which is most of what actually goes wrong.
    ConnectorNo auth
  • Lists every UI component in the project's design system, each with its name, source package, import path, and a short note on its intended use. Read-only and unpaginated: it returns the whole catalog across all packages assigned to the project, so expect a large response on big design systems. Use it to see what exists before building UI, and to get the exact component name other tools need. Do not use it to find a component by need - search_components ranks by description - and do not use it for props, examples, or Figma data, which only get_component returns. project_id is not a display filter: it selects the assigned packages, so two projects in one organization legitimately return different catalogs.
    ConnectorNo auth