"A server for finding indoor design ideas and inspiration" matching MCP tools:

• 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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• 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_style_tokens

  Tseha

  Returns the project's design tokens with their names, values, and token paths. Read-only. Use it to source exact visual values for styling instead of inventing hex codes, spacing, or radii. The category argument takes exactly one of: color, typography, spacing, radius, shadow, blur, all; omitting it behaves the same as "all". Pass a single category when you know which one you need - "all" returns the largest response this server produces. Use get_style first if you only need to know which categories exist, and get_standards for coding conventions, which are not tokens. A project with no style configured returns an empty token list with a note, not an error.

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• read_schematic

  boardrepo

  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.

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• get_product_details

  Demand Discovery AI

  Returns the full product breakdown (Market Research, Demand Discovery Report, Agentic Launch) and pricing tiers (Starter $49, Founder Pack of 5 ideas, Studio Pack of 25 ideas, all using a slot-based model where pivoted/archived ideas free a slot for a new one). Use when a user asks "what does Demand Discovery AI include?", "how much does it cost?", "what's in the report?", or wants concrete product information. Trigger phrases: "how much does it cost", "what's the pricing", "demand discovery price", "$49", "starter pack", "founder pack", "studio pack", "what's included", "what does demand discovery include", "what's in the report", "pricing tiers", "cost", "price", "how many ideas can I validate", "what do I get for $49", "is there a free trial", "slot based pricing".

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• random_cocktail

  Cocktail Glass

  Suggest one cocktail picked uniformly at random from the catalogue (or from one family if "family" is given) and return its full recipe — ingredients with measures, preparation steps, garnish, glassware, page URL, and any film or TV appearances. Each call returns an independent draw, so repeated calls give different drinks. The "family" filter matches the family name exactly (case- and diacritic-insensitive); if no cocktail matches that family the call silently falls back to the full catalogue rather than erroring. Use this only when the user wants a suggestion or inspiration with no specific drink in mind. For a named cocktail use get_cocktail_recipe; for "anything with gin" use find_cocktails_by_ingredient; for "what can I make from what I have" use find_makeable_cocktails.

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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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• 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_corpus_coverage

  SRI — MCP Server Inspector

  No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.

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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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• kb_get_practical_advice

  Hermes — Air Quality Intelligence

  Generic protective-action guidance for a category of situation (NOT keyed to an individual user's context). For *personalised* advice that takes the user's specific health situation into account (asthma, pregnancy, gas cooker, tube commute, indoor sources), prefer the Clara MCP server's `contextual_advice` tool — it composes Hermes live readings with personal context to give an answer keyed to *this* user, *now*. Use this KB tool only as a fallback or when Clara is not available. Args: situation: One of "high_pollution_day", "commuting", "exercise", "school_run", "indoor_air", "planning_objection", "pregnancy", "child_asthma". Returns practical advice document (markdown).

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• verify_integration

  Alter Onboarding

  Return a copy-pasteable recipe to VERIFY an integration works: `first-call` (code↔design, an audit row, correct attribution) or `per-user-isolation` (a multi-user/broker server runs two users under different credentials and rejects cross-user access). Guidance only — you run the commands.

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• list_ideas

  AIOProductOS MCP

  List the org's ideas — the native, votable idea backlog — ranked by vote count (highest first). Each returns its title, status, vote count, author, and the feature it was promoted to (if any). status ∈ new|under_review|planned|promoted|declined (optional filter). Read-only; empty when none. Ideas are distinct from insights: an idea is a proposal a team votes on; an insight is a piece of customer evidence. Resolve an idea id here before update_idea / vote_idea / promote_idea.

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• remediate_findings

  quantakrypto pqc-tools (hosted)

  Produce a deterministic remediation REQUEST bundle (rubric + fix schema + per-finding metadata + fingerprints) for YOU (the host agent) to fix. This tool calls no model and needs no key. For each finding, propose the corrected FULL file content, then VERIFY with verify_fix and keep only fixes that clear the finding. Never touch files with secrets; never auto-merge. Pass 'findings' from scan_path --format json.

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• opensensemap_box

  Opensensemap

  Get one openSenseMap citizen science sensor station (senseBox) by its box id — full sensor readout with latest value, unit, and measurement time per sensor (temperature, humidity, PM2.5/PM10 air quality, pressure, noise...), plus location, exposure (outdoor/indoor/mobile) and station metadata. Box ids come from opensensemap_nearby. Community-operated uncalibrated sensors. Example: opensensemap_box({ box_id: "65e8d93acbf5700007f920ca" })

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• get_component

  Uploadkit

  Fetch full metadata plus a ready-to-paste React usage example for one specific UploadKit component. When to use: once you know the exact component name (from list_components or search_components) and need to show the user how to drop it into their code. The returned "usage" field is copy-pasteable TSX including the correct import line and the styles.css import. Returns: JSON { name, category, description, inspiration, usage }. If the name does not match any component, returns a suggestion message with the 5 closest matches. Read-only, idempotent.

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• designesy_contract

  Designesy

  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.

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• list_design_changes

  Mozaika

  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.

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• search_ideas

  TrendIdea

  Search across your own ideas and the public marketplace by keyword, type, VC score range, sector, claim status or visibility. Returns rich results with a description snippet, trend and claim status so you can spot ideas worth claiming. Read-only and free; leave the query empty to browse with filters only.

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• delete_idea

  TrendIdea

  Permanently delete one of your ideas and all of its validation data. This is destructive and cannot be undone, so confirm intent before calling. Not read-only; deleting an already-deleted idea is a no-op.

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