"A tool for collaborative design and prototyping" matching MCP tools:

• designesy_readiness_score

  Designesy

  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.

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• get_fabrication_quote

  Agentic Fabrication Network (AFN)

  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.

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• find_funders_for_peers

  foundation-discovery

  Find grantmakers that have ACTUALLY funded organizations LIKE the caller's, using the real 7.5M-edge who-funds-whom grant graph (IRS 990-PF, 2022-2026). This is the strongest free-tier prospecting move: collaborative-filtering peer prospecting, distinct from search_funders (name/topic lookup) and search_open_grants (active RFPs). HOW IT WORKS: for each peer organization, it looks up every foundation that granted to that peer, then merges funders across peers. A funder that gave to several of your peers ranks highest. Every result carries real grant evidence — which peers the funder funded and for how much. INPUTS (provide one): - peer_orgs (PREFERRED): names or 9-digit EINs of organizations LIKE the one you're raising for — peers, aspirational orgs, or orgs with a similar mission. The graph is keyed by recipient EIN, so naming real peers yields the sharpest evidence. Up to 12 are used. - org_description: a plain-language description of the nonprofit (mission, cause, who it serves). Fallback that resolves well-funded peers by keyword over the IRS BMF; prefer peer_orgs when you can name a few peers. RECOMMENDED WORKFLOW: establish the org's mission/cause, then name 2-5 peer organizations and call this tool. Deepen any candidate with get_funder_profile / get_foundation_grants (pass the returned ein).

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• compose_landing

  Layero

  Drive the 3-step quiz flow and produce a complete landing. This is the **main entry point**. Don't ask the user questions in chat before calling this — the tool opens native quiz dialogs in the IDE itself. Call this immediately when the user describes what they want. The three quizzes are: 1. **Motivation** — what's being built, for whom, the desired action. 2. **Look & feel** — palette, tone, optional references. 3. **Final picks** — design system (top 3 matched), where submissions go, project name slug. Returns a ``ComposeResult`` with the file bundle to write to disk. The agent then writes the files using the IDE's filesystem tool and proceeds to integration setup / deploy.

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• log_pack_observation

  kubik-tools

  Logs a real, observed consolidation pack -- "these articles, at these quantities, actually packed onto N pallets at these dims/weight" -- against an existing consolidation group in your team's Library. This is ground truth: it becomes a new data point resolve_quantities and the app's own resolve flow learn from (PRINCIPLES.md P-13). Two-step by design: call once WITHOUT confirm to preview exactly what would be logged; call again with confirm=true and the preview_id to actually log it. A confirmed log can be undone within 15 minutes via undo_change -- after that it's permanent (append-only ground truth, by design -- see PRINCIPLES.md P-17/P-18 for why). On the confirm call, only api_key, confirm, and preview_id are actually read -- every other field is required by the schema for shape-consistency but ignored if resupplied, since the values captured during the preview call are what gets logged; to change any of them, call again without confirm for a fresh preview. Do not use this for a single article's own packing history outside a consolidation group -- that data comes from the app's own data entry, not this tool. Do not use this to correct a mistaken past observation after the 15-minute undo window -- log a new, correct observation instead; past ones are never edited. Requires an EXISTING consolidation_groups id -- this tool cannot create a new consolidation group. Requires an existing consolidation_groups id (from the app's Consolidation Groups screen) and each member article's number (resolved to its profile automatically).

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• create_mail_quote

  PostAgent

  Verifies the recipient and sender US addresses and locks a 15-minute USDC price for a documentId. Does not charge or mail anything. Returns a `paymentUrl` (a per-quote x402-payable URL); the preferred way to actually mail the letter is for the agent's wallet to perform an in-band x402 payment against that URL (e.g. `npx awal@latest x402 pay <paymentUrl>`). The MCP `submit_paid_mail_job` tool is a fallback for clients that can emit a standalone signature header. In all cases, show the recipient, sender, options, selected-route `design` constraints, price, AND any `fulfillment.warnings` to the user and get explicit confirmation before paying. The response includes a `fulfillment` block with `requested` (what you asked for), `selected` (what will actually be printed/mailed) and `warnings` (any soft-preference downgrades — e.g. `service_level_downgraded` or `extra_service_unavailable`); do not pay through a non-empty warnings list without re-confirming the trade-off with the user. The response also includes a provider-neutral `design` block; inspect it and the preview before paying because the selected delivery method determines print address/no-ink zones.

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• designesy_design_review

  Designesy

  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.

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• edit_session

  Keyboardia

  Make one narrow, retry-safe edit to an existing collaborative session. After every attempt, the next Keyboardia call must be get_session for the same session. A successful call includes a backwards-compatible compact snapshot plus an acknowledgement. That snapshot is not authoritative verification; do not make another edit or finish from it. Read with get_session next. Supported operations: add_track, set_track_instrument, set_track_pan, set_steps, and set_tempo. set_steps changes only the named steps; it never replaces a track or session. set_track_instrument replaces only a track's sound source, keeping its pattern, mix, timing, and custom name.

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• optimize_flow

  CNAPS.ai MCP Server

  Analyze a flow for performance and cost optimization opportunities. Returns rule-based suggestions such as moving upscale nodes to the end of the flow, avoiding resolution overflow, removing redundant processing, and choosing better-performing models. Each suggestion carries a structured patch (move_node, insert_node, replace_model) describing the change. These are advisory: no MCP tool edits a flow's graph, so apply them by rebuilding the flow with create_flow in the corrected order, or relay them to the user for the cnaps.ai editor. update_flow changes node parameters only. Use this before running a flow or while iterating on its design. Set include_llm_analysis=true to also ask Haiku for complex-pattern refinements.

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• designesy_compare

  Designesy

  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.

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• get_design_history

  Mozaika

  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.

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• ct_search

  Clinicaltrials

  Search ClinicalTrials.gov for clinical trials — find trials and look up a NAMED trial by keyword, condition, drug/therapy, status (e.g. 'Recruiting'), or phase (e.g. 'Phase 2'). Use for "clinical trials for <disease/drug>", or to locate a specific study like "the FLOW trial", "semaglutide kidney outcomes trial" (use ct_get_study for its full design/results). Returns NCT IDs, titles, status, enrollment, and sponsor info.

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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. 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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• create_mail_quote

  PostAgent

  Verifies the recipient and sender US addresses and locks a 15-minute USDC price for a documentId. Does not charge or mail anything. Returns a `paymentUrl` (a per-quote x402-payable URL); the preferred way to actually mail the letter is for the agent's wallet to perform an in-band x402 payment against that URL (e.g. `npx awal@latest x402 pay <paymentUrl>`). The MCP `submit_paid_mail_job` tool is a fallback for clients that can emit a standalone signature header. In all cases, show the recipient, sender, options, selected-route `design` constraints, price, AND any `fulfillment.warnings` to the user and get explicit confirmation before paying. The response includes a `fulfillment` block with `requested` (what you asked for), `selected` (what will actually be printed/mailed) and `warnings` (any soft-preference downgrades — e.g. `service_level_downgraded` or `extra_service_unavailable`); do not pay through a non-empty warnings list without re-confirming the trade-off with the user. The response also includes a provider-neutral `design` block; inspect it and the preview before paying because the selected delivery method determines print address/no-ink zones.

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• principles.search

  AI Design Blueprint

  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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• set_design_overview

  Forge Engine

  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.

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• get_clinical_trial

  Scite

  Fetch full details for a single clinical trial by NCT id. Use this after `search_clinical_trials` when you need the complete record for a specific trial, including the full `description`, study `design`, `enrollment`, `outcomes` (primary/secondary), full `eligibility` inclusion/exclusion criteria, `reportedEvents` (adverse events when the trial has posted results), principal investigator (`pi`), `contacts`, `citations` (related publications), and `resultsUrl`. The search tool returns a slim summary to save tokens; call this tool for a specific NCT id when you need those verbose fields for deeper analysis or patient-trial matching. **Parameters:** - id: NCT identifier (e.g. `NCT02986230`). **Returns:** A compact detail record preserving all trial fields except the low-signal `ontology` classifications.

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• get_service_packages

  Clutch.co

  Use this tool when the user wants to see service packages with fixed pricing and scope for a specific type of service. This tool returns standardized packages offered by service providers, including pricing tiers, deliverables, and delivery timelines. Do NOT use this tool for custom project questions (e.g. "How much would it cost to build a custom app?"). It only returns providers' pre-defined, fixed-price packages, not a quote tailored to a specific project; use recommend_service_providers for those needs instead. Examples: - "Show me SEO packages" -> service="SEO" - "What web design packages can I get for $5,000?" -> service="Web Design", budget=5000 - "Marketing packages from agencies in New York" -> service="Digital Marketing", location="New York" Use `page`/`limit` for pagination.

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• view_dxf

  Aspicio

  Open an interactive viewer the user can pan, zoom, and toggle layers in (renders in-chat on MCP Apps-capable hosts). Reads DXF and vector PDF; for a PDF it shows line work and text rather than a page facsimile, so images, shadings, and transparency are absent by design. Use this when the user wants to see or explore the drawing themselves; for your own analysis use a describe_* tool (facts) or a render_* tool (image). The viewer shows only the drawing from this call. Delivery is handled by the widget itself: small drawings are embedded in the result and larger URL-sourced drawings are fetched by the widget through its own tool call — never re-fetch or inline the file for the viewer's sake, and don't blind-retry if the user reports an empty viewer (the viewer posts its actual status back to the conversation context).

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• sygnl47_subscription_plans

  sygnldata — market intelligence for trading agents

  FREE: prepaid-pass plans for SYGNL/47 (the subscription catalog). x402 is per-call by design. A subscription here is a PREPAID TIME-BOXED PASS on the same rails: one payment buys unmetered access to one tier for one window and returns a signed bearer token, which you then send as X-SYGNL47-TOKEN instead of paying per call. Lists each plan with its tier, duration, price and the exact routes it authorizes. Read this before calling any sygnl47_subscribe_* tool.

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