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750,945 tools. Updated 2026-11-06 12:13

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

  • List the teams that reach the active project and with which role. The other direction of list_team_projects — this is the tool for 'who can write here'. Requires project context. Read-only: members, roles, teams and SSO are not changeable through MCP by design — a human does those in the web app.
    ConnectorAPI key
  • Returns the plain-language meaning and step-by-step fix for one Malinois finding. Use it while helping the user fix an issue reported by scan_app, or when they ask what a finding means. Pass the rule_id exactly as scan_app returned it. Read-only, no network, instant.
    ConnectorNo auth
  • Search 1,000+ vetted AI use cases by keyword, industry, or business workflow (e.g. 'invoice', 'dental', 'customer support'). Use when someone asks how AI can help their business, wants AI ideas for an industry, or looks for automation opportunities. Also use it to find the slug before get_agent_playbook or run_agent. Returns titles, summaries, and links. Public: no sign-in.
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  • 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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  • 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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  • 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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Matching MCP Servers

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    Searches top design platforms like Dribbble and Behance to provide UI inspiration, color palettes, and layout patterns via the Serper API. It allows users to retrieve visual references, articles, and style guides directly within any MCP-compatible client.
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Matching MCP Connectors

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

  • Design Feeds MCP.

  • Rewrite Tailwind CSS classes into their canonical short form. Turns arbitrary values back into real design tokens: p-[1rem] becomes p-4, rounded-[24px] becomes rounded-3xl, -bottom-[4px] becomes -bottom-1. Backed by 12,438 replacements generated from Tailwind 4.3.3's own design system, so the answers are authoritative rather than guessed. Handles one class at a time and does NOT merge across classes (px-4 py-4 into p-4, w-6 h-6 into size-6) — that needs the surrounding group to be safe to collapse; use NormWind for that.
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  • Applies the buyer's field values (and logo, if the template needs one) to a template, fits the text to its printable area, renders both sides as preview images, and returns a design token. Before creating a guest design, explain: unpaid, unsaved drafts expire 30 days after the design request starts. Verified saving keeps the draft; checkout and unresolved purchase artwork is protected. Seven-day token expiry is separate from deletion. Call list_business_card_templates first and collect a non-blank value for every field it lists, keyed by `attribute`; a blank or missing value fails with missing_required_fields. Pass a public https PNG or JPEG URL as `logoUrl` only when the template has an imageUrl field; omit it otherwise. Returns designToken, designId, templateId, revisionId, expiresAt (7 days out), previews (a 300-second signed URL plus width/height for each side; the pixels are also attached as image content blocks), and any text_shrunk warnings from fitting a value to its layer. Present both attached proof images directly, or provide labeled front/back links to the exact preview URLs if the host cannot display them. Do not require computer setup, downloads or re-uploading for proof review. Refresh expired links rather than creating another design. An accountOwned result identifies a verified customer, not an integration key. Results also include a private saveUrl for browser ownership verification; offer it only when the buyer wants to save. Saving requires sign-in; subsequent checkout of that design requires an AI connection authorized by the same InkFE account. If customer OAuth is unavailable, complete checkout before saving. Use a stable requestId; retry the same request after a timeout. Revise with revise_business_card_design and refresh expired links with refresh_design_proof. Show both previews and warnings, get exact print options and get_quote, then record explicit customer approval with approve_design_proof before create_checkout. Fails with unknown_template, missing_required_fields {attributes}, unknown_field {attribute}, value_too_long {attribute}, unsupported_characters {attribute}, logo_required, logo_fetch_failed, logo_unsupported, rate_limited {retryAfterSeconds} (too many designs from this API key in a short time), or connector_unavailable.
    ConnectorNo auth
  • Only for anonymous callers when guest access is enabled. If this AI app is already connected through InkFE customer sign-in (OAuth) or a provisioned integration key, skip this tool and omit guestToken on design/checkout calls. Before guest designing, tell the customer: unpaid, unsaved guest drafts expire 30 days after the design request starts; save through verified sign-in to keep them. Checkout or unresolved purchase records are protected. Returns a private guestToken valid for seven days; token expiry is separate from draft retention. Pass it to create_business_card_design and create_checkout in this conversation. Claimed designs require an AI connection authorized by the same InkFE account. Starting a session does not place or pay for an order.
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  • Get resolved preference values for the caller in this workspace. Each key resolves to the caller's own override when they have set one, otherwise the workspace-wide default, otherwise it is absent from the result. Known keys: connector_write_trust, invoice_default_layout, invoice_design, action_trust, preferred_name, form_of_address, mail_sender_choice, timezone, bank_account_offer, invoice_payment_account, invoice_card_payment_link, payment_link_reconnect_offer, sunday_routines, message_policy, proactive_messages, touchbase_afternoon, touchbase_eod, touchbase_afternoon_workspace, touchbase_eod_workspace, customer_facts_note_id, extension_install_offer, cash_scope, missing_invoice_duplicate_verdicts, todo_kind_mutes, customer_answers_alone_topics, pre_meeting_note, bank_connect_offer, email_weekly_digest, email_connection_updates, email_well_notifications, brief_section_header, brief_section_cash, brief_section_carousel, brief_section_agenda, brief_section_todos, brief_section_tomorrow-meetings, brief_section_business-watch, brief_section_detail, brief_section_main-button, brief_email, unassigned_task_default. Pass `keys` to limit the read to specific keys; omit it to get every preference currently set. A key with no value set anywhere is simply absent from `preferences`, never returned as null or an empty string. `invoice_design` comes back as the invoice design options object `{ layout, theme, locale, payment_terms_note_id, tax_rate_id, legal_mentions_note_id, payment_means_id }`, the same object `well_generate_document` takes as `design`. To save it on an invoice with `well_update_invoice_design`, convert each key to its `design_*` attribute (`layout` → `design_layout`, `payment_means_id` → `design_payment_means_id`, …). Pass `namespace` to read the values saved for one subject, e.g. `"customer:<company_id or person_id>"` for one customer's invoice design. A namespaced read returns only that namespace's values and never falls back to the un-namespaced ones; read without `namespace` too when the house default should apply. The pre-meeting note is off until the member's `pre_meeting_note` is "on", whatever the schedule list shows; an un-namespaced read always returns it as "on" or "off". `mail_sender_choice` is a member-private key read one sender at a time: pass `namespace` set to the `namespace` that `well_list_mail_senders` returns for that sender, and it comes back as `{ choice, sender }` from the caller's own saved row only. No other member's choice and no workspace default is returned for it. To read the choices of many senders at once, call `well_get_mail_sender_choices`. A read without `namespace` also returns `invoice_layouts`: every invoice design, as `{ layout, name, description: { fr, en } }`, the default design first. Name a design to the user only with its `name` and its `description` in the conversation's language, and save the `layout` of the one they pick. When the token authorizes one workspace, call this directly — no workspace call is needed first. When it authorizes several, this read will not guess which one you mean: pass `workspace_id` on the call.
    ConnectorNo auth
  • Keywords one competitor ranks for in the top 100 that the target does not rank for at all. Use when: "what does competitor.com rank for that we do not", "find gaps against X", content opportunities from a rival. Not for: everything a domain ranks for, use seo_get_ranked_keywords. Finding who the competitors are, use seo_get_serp_competitors. Fresh ideas around a topic, use seo_search_keywords. Returns: List. rows[]: keyword, competitor, competitor_rank, competitor_url, volume, kd, cpc, intent. Sorted by volume. Cost: 5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days. Example: {"target": "example.com", "competitor": "competitor.com", "limit": 100}
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  • Planning-time statistical power from a design's REAL model matrix — no data needed. Builds the design and takes `ncp = effect_size² / (X'X)⁻¹_jj`, so it is correct for centre points, axial points and unbalanced designs — unlike `covadoe_power_analysis`, which assumes orthogonality and overstates power on a CCD, Box-Behnken or DSD. Use this when planning an experiment; use `covadoe_post_hoc_power` only once you have measured responses. `design_type` + `n_factors` builds the design (same generator as `covadoe_create_design`, so the answer describes the design you would actually get). Common aliases resolve ("full_factorial", "ccd", "dsd"). Alternatively pass `design`, an explicit coded run matrix, to score a design you already hold — D/I-optimal, mixture, split-plot or hand-built. `n_runs` / `model_terms` are forwarded to the generator for the optimal designs. `model`: "linear" | "interaction" | "quadratic" | "quadratic_no_interaction" (a DSD supports only the last). `term` names the coefficient — "x1", "x1^2", "x1*x2"; omit it to get power for every term and group, which differ sharply on the same design. `alpha` is the significance level; the CCD axial distance is `axial_alpha`, and the two are easy to confuse. CCD variant: `axial_alpha` defaults to ROTATABLE, (2**n_factors)**0.25 — the design JMP, Design-Expert and Minitab hand you. Pass a number, or "orthogonal" for the α where Σx² = n_runs (at 3 factors: main-effect power 0.9400 against the rotatable 0.8846 on the same 17 runs; the orthogonal α is also the premise of `covadoe_power_analysis`, so on that design the two agree for a main effect and disagree for every other term). `face` — "circumscribed" (default), "faced" (star points on the faces, α = 1) or "inscribed"; a bool works, and an unknown value is rejected rather than quietly treated as circumscribed. Returns power, power_by_term, power_by_group, df_error, relative_variance ((X'X)⁻¹_jj), the resolved design_summary (the α and factorial level actually built — read both, an inscribed CCD always reports α = 1), and `orthogonal_shortcut_power` — what `covadoe_power_analysis` would have claimed — with its signed error (signed: the shortcut does not always overstate). Returns `estimable: false` plus a reason when the model cannot be fitted on the design.
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  • Amazon search ideas around a seed, from Amazon's related searches, with monthly Amazon search volume. Use when: "what else do people search on Amazon around X", building an Amazon keyword list for a listing or ads. Not for: Google keyword ideas, use seo_search_keywords. Volume for keywords you already have, use amazon_get_keyword_metrics. Returns: List. rows[]: keyword, volume. Cost: 5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days. Example: {"seed": "standing desk", "limit": 50}
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  • Publish a site to make it live on the web at its platform address (the `deployment_url` in the response is the exact live URL — report that, never guess a host). Choose a subdomain matching the business name (lowercase, hyphens). IF THE SITE STILL HOLDS SEVERAL DESIGNS you MUST pass `variation_id` — the design to publish, taken from list_variations (a UUID, not an index). Do not choose for the user: list_variations attaches a thumbnail of each design, so show them and let the user pick. Publishing a design turns it into its own site: Mondovo builds the chosen design into a new site and publishes THAT, so the response carries a different `site_id` — use that id from then on (the original id stays the design draft, and get_site on it will keep saying unpublished). Calling publish twice reuses the same built site rather than creating another. Sites that already have one design ignore `variation_id`. A design only has its home page, but its menu links to the rest of the site: when it does, publish_site first BUILDS those pages and then publishes automatically — it returns status "building" with `pages_being_built`, a `job_id` and the new `site_id`. Before publishing a design, tell the user which pages its menu links to and that they will be built. On "building", tell the user which pages are being built, poll get_job with the job_id until "completed" (`failed` lists pages that could not be built — their menu links are removed; `publish` says whether the site went live), then poll get_site until "published". Do not call publish_site again meanwhile. If a response carries `missing_pages`, those menu links have no page and 404 on the live site: tell the user and offer add_pages for them. This tool RETURNS IMMEDIATELY with status "publishing" once the site is accepted for deployment — it does NOT wait for the deploy. Compiling and deploying takes 1-3 minutes and continues server-side even if this conversation ends. Poll get_site (with the returned site_id) every ~15s until status is "published" to get the live URL — or "publish_held", which means the new build crashed in a browser check before going live and was not published (tell the user its `publish_message`). NEVER call publish_site a second time to check on or hurry along a publish you already started: while one is in flight the publish lock rejects the call, and a transport timeout on this tool does NOT mean the publish failed — it is almost always still running, so poll get_site before concluding anything. If the response is `contact_info_needs_confirmation`, its `reason` says why: "placeholders" means contact details that look AI-invented (listed in `placeholders`) — refine them to the real values first, or (if they are already correct) call again with `confirm_contact_info: true`; "missing_details" means nothing was invented but the email or phone in `missing_fields` is absent — ask the user for it, or call again with `confirm_contact_info: true` if the site should go live without it. Never make up a contact detail. Retrying with the same arguments will NOT clear that warning. Success responses carry `after_publish` (plan, custom domain, editor link): once get_site reports "published", relay its `tell_user` to the user.
    ConnectorOAuth
  • Design up to four icon ideas for the site's browser tab, bookmarks and search results, from its brand name, colours and heading font, plus the plain letter icon ("monogram"). One AI image; options are cached per site, so calling again returns the same set unless `regenerate` is true. Ideas whose lettering does not match the brand are dropped. Returns preview URLs — show them, then call set_favicon with the chosen id.
    ConnectorOAuth
  • Use this to put a Pin back to the original photo the design was built from, discarding the generated design. Free and instant. Only works when get_pin_design lists "revert" in supportedOperations, which requires the Pin to still carry its original photo. The generated variations remain available, so this is reversible with select_pin_design_variation. If the user did not say which Pinterest account to use and list_accounts returns more than one, ask the user which account to use before calling this — do not choose for them.
    ConnectorOAuth
  • List security/safety findings for your workspace, most recent first. Optionally filter by status, target model, minimum severity, or a specific run. Returns a compact summary; call get_finding for the repro detail of any one finding. On a plan that withholds a finding's proof, category reads '[redacted]' and get_finding returns the same — the finding and its severity are real, the evidence is withheld. Paginated: 200 findings per page (max 200). The result carries total_matched and, when there is more, next_cursor: pass it back as 'cursor' with the same filters (it is bound to them) to read the next page, until it is absent.
    ConnectorOAuth
  • `get_planning_signals` — what is HAPPENING around Scripe profiles, for planning from evidence, in ONE bounded call (up to 10 profiles; omit `profileIds` for every profile you can reach). Returns: (1) `niche` — what works on LinkedIn right now among people like each profile: recent posts by OTHER people that beat their own author's usual engagement (`outlierMultiple`), with opening, format, lane, author and link, each listed once with the `profileIds` it is relevant to; (2) `sourceItems` — what the profiles' followed sources published since `sourcesSince` (default 7 days ago), with each profile's match score and the For You idea it already became; (3) per profile `performance` — THE source of performance numbers: its own posts of the last 90 days by post format (with lane), lane, media format and content topic, each with a `lift` against that profile's own median, headed by `summary` — what performed for that profile, in words: plan more of it and say what you learned; quote a lift from the profile it sits under; (4) per profile idea stock — `forYou` (the strongest unsaved For You ideas per lane, WHY Scripe picked each and its source) and `board` (unplaced board ideas); raise `ideasPerLane` for a long plan instead of paging `list_for_you_ideas` per profile; (5) `knowledge` — knowledge-base documents added in the last `knowledgeDays` (default 30: meetings, interviews, files, synced docs), each with its opening (a recording's chapters) and the profiles that can use it; (6) `knowledgeSummaries` — per profile the most relevant document Scripe already summarised (its own first, then the one matching its content topics; last 180 days): every chapter with its summary, or a meeting's own summary — cite it by name in an idea's notes; read one whole with `read_knowledge_document`. Nothing is ranked or chosen for you: weigh it yourself, then write ideas in `preview_plan`. `include` narrows the sections; `detail: "full"` widens every list. Every answer stays under a host's inline limit: `trimmed: true` says list tails were cut — ask again for fewer `profileIds` or a narrower `include`.
    ConnectorOAuth
  • Fresh trade ideas from the top-N current Buzzberg authors. Two filters combine: 1. AUTHOR filter: only top-N by the default 30-day Authors ranking. 2. SIGNAL filter: by default only FIRST (speaker's first mention of a ticker) and FLIP (speaker reversed direction on a ticker) — the same high-signal slice that the /trade-ideas?first=1 feed surfaces. Use this to answer "what new ideas did the best speakers float in the last 24h / 7d / 30d?" in one call. Do NOT use it for "best/new ideas across Buzzberg": it intentionally excludes non-top-ranked speakers and defaults to First/Flip signals only. Use `get_recent_idea_candidates` for a complete recent candidate pass. Scope with top_n/limit; prefer one broad call, then targeted follow-ups. Args: top_n: Rank speakers by alpha and keep the top N (1-200). Default 50. window: Lookback for ideas. One of: 1h, 6h, 12h, 24h, 1d, 3d, 7d, 14d, 30d, 60d, 90d. Default 7d. signal: "first_flip" (default — first+flip, matches site's First Only), "first" (strictly first mention), or "all" (no signal filter, returns every idea from top speakers in window). direction: "long" / "short" / "avoid" / "neutral" / "" (all). Default "". source_type: youtube / twitter / newsletter / reddit / news / "" (default excludes news wire feeds — pass "news" explicitly to include). limit: Max ideas in response (1-100). Default 30.
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  • Delete layers from a design, with everything inside them and their motion. Returns the deleted layer ids (and any `skipped` with skip_missing). If one id is not on the design the call is refused and nothing is deleted. Saved as a new revision: undo brings the layers back, but only until the next change is undone past. Use it to remove layers the design no longer needs; to hide one for now set visible: false with update_layers, and to remove a whole page use delete_page.
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    Destructive
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  • Create one or more findings in Mallory. A finding is a durable record that a specific problem exists on a specific asset belonging to the caller's own organization — not a chat message and not a note to yourself. It is visible in the Mallory UI to everyone in that organization, and nothing on this server deletes one: a finding filed by mistake can only be marked dismissed with updateFinding. WRITES IMMEDIATELY. There is no draft, no preview and no confirmation step — calling this tool IS the write. Only call it when the user has asked, in so many words, for findings to be filed in Mallory ("create a finding for that", "file these"). Finishing an investigation is not permission to file its results: report them and let the user decide. WHAT TO SEND - definition_slug must ALREADY EXIST in the catalog. Look one up with the queryApi tool, path "/v1/finding_definitions" (filter by category or severity to narrow). Never invent a slug, and never substitute a near-match for one that was rejected — that files the wrong kind of finding. - One finding per problem per asset. Five misconfigured buckets are five findings sharing a definition_slug with five different asset_identifier values, not one finding listing five buckets. Send the whole batch in ONE call (max 25): each is created independently, so one duplicate does not block the rest. - asset_type is a provider.service.object value (e.g. aws.s3.bucket, aws.iam.role, github.repo, azure.storage.account), or "generic" when nothing fits. Legacy underscore forms like "s3_bucket" are rejected. - summary / body / remediation are markdown, and are read by people who were not in your conversation: what is wrong, how you established it, and the actual fix. - evidence is one entry per thing you actually OBSERVED — the query and what it returned, the endpoint and its status, the file and the matching line. Three observations are three entries. Never write evidence for something you inferred rather than observed; lower confidence and say so in body instead. ENUM VALUES ARE CASE-SENSITIVE AND EACH FIELD HAS ITS OWN SET. severity is UPPERCASE (CRITICAL, HIGH, MEDIUM, LOW, INFO) and optional — omit it and the definition's own default applies, which is usually right; override only when this instance is genuinely worse or milder than the type normally is, and say why in body. confidence is lowercase (low, medium, high). Status is not settable here: a finding is created open, and status values are lowercase (see updateFinding). OUTCOMES come back per finding, in `created` and `failed`: - DUPLICATE — an open finding already covers that asset, and `existing_finding_uuid` names it. Say so and move on. Do NOT re-word the title and retry; to change the one that exists, call updateFinding with that uuid. - UNKNOWN_DEFINITION — the slug is not in the catalog. Look up a real one; do not guess a neighbouring slug. - INVALID — core rejected a field, most often asset_type. Fix that field, not the slug. - INVALID_ASSET_IDENTIFIER — asset_identifier names no asset (a placeholder such as "unknown", or a bare word such as a tool or data-source name, with asset_type "generic"). Nothing was written. Use the real affected asset from the source data (host:port, hostname, URL, account, repository); never invent one. - PLAN_LIMIT — findings are not included in this tenant's plan. The request was fine, nothing is broken and nothing was written: tell the user, pass on the upgrade link if the outcome carries one, and do not retry or reach for another tool to file it. `list_url` is null outside the Mallory chat app — there is no conversation for an MCP call to scope a list to. Read a created finding back with getFinding using the uuid in `created`, or browse the tenant's findings with listFindings.
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