"Ant Design" matching MCP tools:

• search_components

  Uploadkit

  Fuzzy-search the UploadKit component catalog by any free-text keyword — component name, category, description, or design inspiration (e.g. "apple", "stripe", "vercel", "terminal", "progress ring", "kanban board", "matrix"). When to use: the user describes the vibe or use case but does not know the component name yet ("I want something like Stripe Checkout", "show me Apple-style uploaders"). Prefer this over list_components when the goal is discovery rather than enumeration. Returns: JSON { query, count, matches: [{ name, category, description, inspiration }] }. Read-only, idempotent, case-insensitive.

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• perspective_create

  Perspective AI

  Creates a new perspective in DRAFT status from a natural-language description and starts the design agent. Returns immediately with a job_id and status "pending"; long-poll perspective_await_job with that job_id to receive the generated outline or follow-up question. Behavior: - Creates a new perspective on every call — not safe to retry blindly. Identical input produces a new perspective each time. - If workspace_id is omitted, the user's default workspace is used; errors with "No default workspace found..." if none exists. - Tip: use workspace_list to see all workspaces with their descriptions, then pick the best-matching workspace_id based on context. - Title is auto-generated from the description. - The design agent runs in the background and may take seconds to a minute. Resolve via perspective_await_job; terminal states are "ready" (outline generated, share/direct/preview URLs returned) or "needs_input" (follow-up question requires the user's answer). - description can reference research goals, source URLs, or audience details. Examples: "understand why trial users aren't converting", "convert the form at https://example.com/contact", "talk to churned customers from Q3". - agent_context selects the agent role: 'research' = Interviewer (default; deep qualitative interviews), 'form' = Concierge (replaces static forms with conversational flow), 'survey' = Evaluator (turns surveys into engaging conversations), 'advocate' = Advocate (listens, then responds from a brand/cause playbook). When to use this tool: - The user wants to create a new perspective from a brief. - You're starting the design conversation that may iterate via perspective_respond. When NOT to use this tool: - The perspective already exists and the user wants to change it — use perspective_update. - The agent already asked a follow-up question — use perspective_respond with the user's answer. - Listing or finding existing perspectives — use perspective_list. Typical flow: 1. perspective_create → start design (returns job_id) 2. perspective_await_job → long-poll until "ready" or "needs_input" 3. perspective_respond → if "needs_input", answer and re-poll 4. perspective_get_preview_link → test 5. perspective_update → refine 6. perspective_get_embed_options → deploy

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• handoffs.agency

  AI Design Blueprint

  Authenticated — submit an agency engagement enquiry on behalf of the caller for a founder-led discovery call. Persists an AgencyHandoff row routed to the agency inbox; the user is contacted by the team for a scoped proposal. Engagement scopes: workflow sprint (rapid agentic workflow implementation), proof-of-concept (validate a specific agent design in a bounded timeframe), pilot support (co-design and validate a production-ready pilot), advisory (ongoing architectural guidance across a product team). WHEN TO CALL: the user has identified a paid hands-on expert engagement need beyond self-service learning, and explicitly asks to talk to the team or book a discovery call. ALWAYS confirm with the user before firing — this creates a sales-visible record. WHEN NOT TO CALL: for free training / partnerships discussion (use handoffs.partnership); for support / billing / access (use handoffs.operator); proactively or as a sales push. BEHAVIOR: write-only, single insert, side-effecting. Auth: Bearer <token> (Firebase ID token, any plan). UK/EU residency. Response confirms the ticket id + scope so the user can reference it.

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• upload_image

  Real Real Genuine

  Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64, base64-encoded JPEG/PNG, with or without data URI prefix. image_url, publicly accessible image URL (max 5 MB). image_chunks, array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap, resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

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• signals.report

  AI Design Blueprint Doctrine

  Pro/Teams — records a value moment (review_confidence, runtime_risk_found, regression_caught, recommendation_taken) after a successful architect.validate or design session. Each event captures event_type, surface_used (mcp/web/cli), perceived_value (1-5), and an optional brief_context — structured fields only, NO prompts or code stored. WHEN TO CALL: after architect.validate returns a clearly useful result AND the user has acknowledged the value (or you ask them "would you rate this 1-5?"). Validate's response carries an explicit next_step instruction telling the agent to OFFER this call — surface that offer to the user. WHEN NOT TO CALL: silently or without the user's awareness; on every validate (only after a clear value moment); to capture intent or speculative value. If the user declines, do not retry within the same session. BEHAVIOR: write-only, single insert into ValueEvent. Auth: Bearer <token>, Pro or Teams plan required. UK/EU residency. Do NOT include proprietary code, prompt content, or PII in brief_context — it surfaces in admin AI-visibility dashboards. Expect a 1-line acknowledgment in the response; the structured feedback is then aggregated server-side.

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• perspective_await_job

  Perspective AI

  Long-polls a perspective-design job (started by perspective_create, perspective_respond, or perspective_update) and returns either its terminal result or another "pending" envelope to keep polling. Behavior: - Read-only — observes a running design job. Safe to call repeatedly. - Errors with "Unknown job_id" if no such job exists, or "job_id does not belong to a perspective design workflow" if the id is for a different kind of job. Workspace and perspective access are re-checked on every call. - Each call blocks up to wait_ms (default 30s, min 1s, max 45s). On timeout, returns status "pending" with a progress_cursor — pass it back on the next call to skip already-seen progress events. - Terminal status is "ready" (outline generated; share_url/direct_url/preview_url populated) or "needs_input" (follow_up_question populated). Failures surface as "Design job failed: ..." with the underlying message. When to use this tool: - Immediately after perspective_create / perspective_respond / perspective_update returns a job_id. - Re-polling after a previous call returned status "pending" (pass the returned progress_cursor back). When NOT to use this tool: - You don't have a job_id yet — call perspective_create / perspective_respond / perspective_update first. - Inspecting a finished perspective's config — use perspective_get.

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• regenerate_logo

  WebZum - The Hosting Layer for AI-Generated Web Content

  Regenerate the logo for a WebZum site using AI. Creates a new version with a fresh logo and reassembles. Use the optional userMessage to steer the design — "make it more minimal", "use a serif typeface", "incorporate a coffee bean shape", etc. Required: businessId, versionId, pageId. Returns { versionId, status: 'completed' | 'in_progress', ...extra }. If status is 'in_progress', poll get_site_status with the returned versionId every 5-10s until isComplete is true. Concurrency: edits on the same businessId MUST be serial. Never fire parallel edit calls on the same site.

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• delete_thesis

  Valuein — SEC EDGAR Fundamentals & Smart-Money Data

  Soft-delete a saved thesis: status flips to `archived` (the row stays for audit / re-scoring). Idempotent — archiving an already-archived thesis succeeds. Hard-delete is not supported by design; future versions may expire archived theses after N years. This does not delete the claims linked to the thesis — use delete_claim for those. Tier: paid + free (sample rejected).

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• principles.search

  AI Design Blueprint Doctrine

  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.

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• get_store_template_details

  agentView

  Returns the full public details of a single store template: localized title, short description, long-form markdown (intro, use cases, audience, setup), category, optional suite (design family), tags, theme, designStyle, placement, features list, preview image URL, store detail path, AND an agentArtifacts array listing the bot-onboarding files shipped with the template (system prompts, Agent Skills standard SKILL.md files, MCP-config snippets). agentArtifacts is metadata only — bodies live behind get_store_template_agent_artifact (anonymous, raw with placeholders intact) and get_display_agent_artifact (owner-scoped, placeholders substituted against a specific display's installed slot slugs). Use this after search_store_templates picks a candidate so you can explain the template to the user, decide whether it ships agent integration, and offer the right install/onboard flow. No authentication required.

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• mu_preview_mockup

  mu

  See the mockup BEFORE creating any product — nothing is created or sold, and it costs no credits. Renders the design on the real garment (Printful) when the kind supports it (source: "printful"), otherwise a clean MU product card (source: "card"), and returns a durable preview image URL. Optionally pass `position` (front-print DTG apparel only: tee / tee_white / hoodie / crewneck / tank / long_sleeve_tee) to preview a custom print placement — passing the SAME position to mu_create_product prints exactly what you previewed (WYSIWYG). Usually answers in 10-45s; if it returns status="processing", call this tool again with the returned `preview_id` to keep waiting. Rate limit: 30 previews/hour. Requires `Authorization: Bearer <api_key>`.

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• tfgenerate

  InsideOut (Riley)

  WORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NOT call this while convoreply is still running or before terraform_ready is confirmed! If you get 'session has not reached terraform-ready state', wait for convoreply to complete first. 🎯 USE THIS TOOL WHEN: convoreply has returned with terraform_ready=true, OR the user asks to 'see the terraforms', 'generate terraform', 'show me the code', etc. **DEFAULT RESPONSE**: Returns summary table + download URL (keeps code out of LLM context). **FALLBACK**: Set `include_code: true` to get full code inline if curl/unzip fails. **CRITICAL WORKFLOW** (default mode): 1. Call this tool to get file summary and download URL 2. ASK the user: 'Where would you like me to save the Terraform files? Default: ./insideout-infra/' 3. WAIT for user confirmation before running the download command 4. Run the curl/unzip command with the user's chosen directory 5. If curl/unzip FAILS (sandbox, security, platform issues), retry with `include_code: true` **AFTER GENERATION**: Ask user if they want to review the files and then deploy with tfdeploy REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: include_code (boolean) - set true to return full code inline as fallback. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• mu_upload_design

  mu

  Upload a PNG design (base64-encoded, <=3MB decoded) and receive a durable https url. Pass that url as `design_url` to mu_create_product. Requires `Authorization: Bearer <api_key>`.

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• list_components

  Uploadkit

  List every React upload component shipped by @uploadkitdev/react with its name, category, one-line description, and design inspiration. When to use: before recommending or scaffolding any UploadKit component, to confirm the exact name exists and to pick the right variant for the user's context (e.g. browse all "dropzone" variants when the user wants a drag-and-drop area). Returns: JSON { count, components: [{ name, category, description, inspiration }] }. Read-only, no side effects, idempotent.

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• send_html

  agentView

  Pushes raw HTML to one display, replacing current content. Prefer send_url only when the user explicitly wants an external web page. Include a human-readable description so get_display_content can summarize intent without reading raw HTML. Before complex content, call get_display_capabilities to match the real browser/runtime. When no design system is supplied, use premium digital-signage quality: full-screen layout, strong hierarchy, refined typography, robust fallback data, and no action buttons unless touch is requested. Exactly one of html or base64_html is required. Requires content_only scope and display management access. Returns id, name, duration, file and version.

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• signals.report

  AI Design Blueprint

  Pro/Teams — records a value moment (review_confidence, runtime_risk_found, regression_caught, recommendation_taken) after a successful architect.validate or design session. Each event captures event_type, surface_used (mcp/web/cli), perceived_value (1-5), and an optional brief_context — structured fields only, NO prompts or code stored. WHEN TO CALL: after architect.validate returns a clearly useful result AND the user has acknowledged the value (or you ask them "would you rate this 1-5?"). Validate's response carries an explicit next_step instruction telling the agent to OFFER this call — surface that offer to the user. WHEN NOT TO CALL: silently or without the user's awareness; on every validate (only after a clear value moment); to capture intent or speculative value. If the user declines, do not retry within the same session. BEHAVIOR: write-only, single insert into ValueEvent. Auth: Bearer <token>, Pro or Teams plan required. UK/EU residency. Do NOT include proprietary code, prompt content, or PII in brief_context — it surfaces in admin AI-visibility dashboards. Expect a 1-line acknowledgment in the response; the structured feedback is then aggregated server-side.

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• capture_screenshots

  TestMyVibes

  Drive a headless Chromium against a URL and return a screenshot for each requested viewport (mobile / tablet / desktop). Optional clickPaths lets you grab the state behind a sequence of clicks (e.g. ['Sign in', '#email', 'Continue']). Pricing: 1 credit per single viewport, 5 credits for the desktop+tablet+mobile triple (otherwise 1 × viewport count). Output: signed Spaces URLs valid for 7 days. Use this for marketing screenshots, design QA, regression-watch baselines — anything where you need pixels without a full AI test.

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• handoffs.partnership

  AI Design Blueprint

  Authenticated — creates a partnerships handoff record for design-partner, ecosystem, training, or advisory conversations needing human review. Persists a PartnershipHandoff row routed to the partnerships inbox; the user is contacted by the team. WHEN TO CALL: user explicitly wants to engage as a design partner, co-marketing/training partner, or evaluate the Blueprint for their org's training programme. ALWAYS confirm with the user before firing — this creates a human-visible partnerships ticket. WHEN NOT TO CALL: for general support / billing / access issues (use handoffs.operator); for paid-engagement enquiries (use handoffs.agency); proactively or as a sales prompt — only when the user has explicitly asked. BEHAVIOR: write-only, single insert, side-effecting (creates a ticket). Auth: Bearer <token> (any plan). UK/EU residency. Response confirms the ticket id + audience so the user can reference it.

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• principles.search

  AI Design Blueprint Doctrine

  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.

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• analyze_weather

  epwforge-mcp

  Compute design conditions, HDD/CDD, monthly stats, and peak heating/cooling days for one or more EPW files. Accepts a `url` (existing EPW), `urls` (compare 2+), or `config` (synthesize on the fly with morphing/UHI/events/smoke). Config mode runs the full generation pipeline server-side but returns only stats — never the EPW content. **Token-saver: pass `compact: true` to get a ~10-field headline response (~100 tokens) instead of the full ~800-token payload.** Use compact for sanity-checking, dashboards, or when chaining many calls; full when you need monthly arrays / peak days / full ASHRAE. Optional `include_full_ashrae` adds ASHRAE 0.4/1/2% cooling + 99.6/99% heating design conditions with mean coincident dewpoint. Optional `include_improbability` (config mode) adds a stress-test score. Optional `include_idf` adds ready-to-paste EnergyPlus SizingPeriod:DesignDay objects. Optional `units` ('imperial' default | 'metric'). **Presentation: when calling with `urls` (multiple files), the response includes a `comparisons` array — render it as a markdown table to the user. Lead with the headline delta, not the raw data.** No auth required; no credits charged.

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