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206,405 tools. Last updated 2026-06-17 13:10

"CSS Modules" matching MCP tools:

  • Full-text search across every UploadKit docs page (88+ pages — getting-started, core-concepts, SDK reference, API reference, dashboard, guides). Ranks matches by keyword frequency in title, description, and body. When to use: any question about UploadKit behaviour, configuration, or integration that the component tools do not answer — middleware, onUploadComplete callbacks, REST API endpoints, webhooks, presigned URLs, CSS theming variables, type-safety setup, migration from UploadThing, rate limits, etc. Returns: JSON { query, count, indexGeneratedAt, matches: [{ path, url, title, description, snippet, score }] }. Sorted by score descending. Read-only. Bundled index (no network call) — results reflect docs at build time.
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  • Given a rack (a set of module ids the user owns), rank the modules NOT in the rack by how many rack members they pair with. The set-level companion to find_compatible_with: where that answers "what pairs with module X?", this answers "given my whole rack, what single module should I add — the one that pairs with the most of what I already have?". The ranking signal is `pair_count` — the number of DISTINCT rack members a candidate pairs with. A module that modulates five of your modules ranks above one that modulates one. This aggregate is the point: you can't get it from per-module find_compatible_with calls without tallying distinct members by hand. Use this for: - "What should I add to a rack with <modules>?" / "what fills out this system?" - "Given these modules, what pairs well with the most of them?" - Inspecting a rack's own internal pairing structure (the `internal` edges). Combination edges only. Ranking uses the seven patch-time relationships (clock-source-for, cv-source-for, modulator-for, audio-source-for, quantizer-for, trigger-source-for, envelope-target-for) — the "A and B work together in a patch" kinds. The substitution/catalog kinds (alternative-to, replaces, expander-for) are deliberately excluded: a pairing recommender shouldn't suggest replacing your modules with each other. For "what's an alternative to X?" use find_compatible_with. Args: - rack (string[], required): module ids, e.g. ["make-noise/maths", "mutable-instruments/plaits"]. Ids that match no module are returned in `unknown_ids` (and in `unresolved` with did-you-mean suggestions) rather than failing the call. Surface those rather than proceeding on a partial rack: the server is stateless about your rack — it keeps no memory of it between calls, so pass the COMPLETE current set every call. Max 64. - relationship (string, optional): restrict ranking to one combination kind above. Omit to consider all seven. - limit (number): default 25, max 100. Returns: { "rack": [{ id, name }], // the rack members that resolved "unknown_ids": [string], // rack ids that matched no module "internal": [{ from_module_id, to_module_id, relationship, source_id }], // edges within the rack "candidates": [{ id, name, manufacturer, pair_count, "pairings": [{ rack_member, relationship, direction, source_id }] // why it pairs, per member }] } `direction` on each pairing is relative to the rack member: 'outbound' = the candidate is the role-bearer (it `relationship`s the member, e.g. the candidate is a modulator-for the member); 'inbound' = the member is the role-bearer. Coverage caveat: rankings are only as dense as module_relationships. A thin or empty result means the corpus hasn't recorded those edges yet, not that no good pairing exists — call report_gap if you expected matches.
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  • Return a canonical definition for a primitive Eurorack / synthesis concept and its relations to other concepts in the corpus. Use this for VOCABULARY questions, not module questions — when the user is asking what a term means or how two terms relate, not which modules implement it. Typical shapes: - "Is four-quadrant mult the same as through-zero AM?" → lookup_concept("four-quadrant mult") - "What's the difference between a gate and a trigger?" → lookup_concept("gate") - "Modular signal level vs line level — when does it matter?" → lookup_concept("modular signal level") - "Are clock dividers just pulse counters?" → lookup_concept("clock divider") - "Are polyphonic patch cables TRRRRRS?" → lookup_concept("polyphonic cable") Lookup is case-insensitive across three axes, tried in order: the canonical id ("through-zero-fm"), the canonical label ("Through-Zero FM (TZFM)"), and any registered alias ("tzfm", "through zero fm"). Spaces and hyphens are matched literally; the lookup does NOT normalize whitespace beyond lowercasing. If the term doesn't match anything, the response includes up to 5 substring-matched suggestions. Args: - name (string, required, min length 2): the term to look up. Examples: "AM", "ring mod", "four-quadrant mult", "TZFM", "clock divider", "gate", "trigger". Returns: { "concept": { "id": "amplitude-modulation", "label": "Amplitude Modulation (AM)", "description": "A multiplication of two signals: the carrier...", "aliases": ["am", "amplitude modulation", "amplitude mod"], "related_concepts": [ { "related_concept_id": "ring-modulation", "related_concept_label": "Ring Modulation (RM)", "relation_kind": "commonly_confused_with", "note": "AM with a unipolar modulator preserves the carrier..." }, ... ], "source_id": null, "citation_url": "https://learningmodular.com/glossary/...", "citation_quote": "Amplitude modulation is when..." } | null, "_meta": { "query": "<the name argument verbatim>", "matched_via": "id" | "label" | "alias" | "none", "concept_suggestions": [ { "id": "...", "label": "...", "matched_via": "alias", "matched_text": "..." } ], "feedback_hint": "...?" } } Relation kinds: - "related_to" — see-also link (default; symmetric in spirit). - "subtype_of" — X is a specific case of Y (RM ⊂ AM, TZFM ⊂ linear FM). - "inverse_of" — X is the opposite of Y (clock-divider ↔ clock-multiplier). - "commonly_confused_with" — they're distinct, but people conflate them (gate vs trigger, AM vs RM, modular level vs line level). When to cite: every concept carries either source_id or citation_url + citation_quote. Surface the citation when the answer affects a decision (e.g. "the corpus cites learningmodular.com — TRS cables are physically the same connector whether carrying balanced mono or unbalanced stereo; only the destination determines the role"). When the result is null and concept_suggestions are provided, present 2–3 closest matches to the user. If none look right, the corpus genuinely doesn't carry that concept — call report_gap with kind="missing_field" and tool_name="lookup_concept" naming the term and its expected definition.
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  • Fetch the full HTML body, CSS, sampleData, and pageOptions for one starter template by slug. Use this when you need to understand the exact shape of `data` the template expects before calling render_template_to_pdf, or when you want to fork a starter into custom HTML. Free, no payment, no auth required.
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  • Publish HTML content to a live URL instantly. No account or API key required. Returns a public URL that anyone can visit. Sites expire after 24 hours unless the owner claims them. Use this when a user asks you to build, create, or deploy a website, landing page, invitation, portfolio, report, or any HTML content they want to share as a link. Supports bundled assets (CSS, JS, images) and multi-page sites (include additional .html files in assets, accessible at /{slug}/{pagename}). IMPORTANT: After publishing, always share the live URL and the claim URL with the user. The claim URL lets them take permanent ownership of the site. Store the edit_key from the response silently — do not show it to the user — you will need it if they ask you to make changes to the site later. If you lose the edit_key, ask the user to claim the site first (via the claim URL in the page footer), then provide you with their API key from the dashboard — you can use that instead.
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  • Run a one-shot SEO + AI-readability audit on any public URL. Returns scores across 11 modules and ~90 checks, plus actionable findings with rule docs. Limited to 1 audit per IP per 24 hours — for higher volume, get an API key at https://app.metricspot.com/settings/api-keys and use `run_audit`. Synchronous: blocks until the audit completes. Does NOT include Core Web Vitals (use `run_audit` for full PSI scoring). No auth required.
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Matching MCP Servers

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  • An MCP server for generating images from HTML & CSS or screenshots of URLs using htmlcsstoimage.com.

  • Easy way to publish static content for free - forever. No hassle way to publish html/css/js, pdf, .md, txt, etc.

  • Return modules that have a typed compatibility relationship with the given module. Both edge directions are returned and tagged via the per-match `direction` field — so a single call answers both "what is X a R for?" and "what is a R for X?". `relationship` is OPTIONAL. Omit it to get EVERY edge touching the module across all relationship kinds — the bare "what pairs with / relates to X?" question — with each match self-describing via its own `relationship`. Pass a relationship to restrict to that one kind. Prefer the relationship-less call when you don't already know which kind exists; reach for the typed form only when the question names a specific role ("what clocks X?"). Use this for two question shapes: 1. Patch-time compatibility — "what could I use as a clock source for X?" (returns matches with direction='inbound'), or "what does X clock?" (direction='outbound'). 2. Catalog comparison — "what's an alternative to X?" (symmetric), "what does X replace?" (outbound) / "what replaces X?" (inbound), "is there an expander for X?" (inbound). The vocabulary describes the edge as stored (from = role-bearer, to = target): Patch-time: - clock-source-for — A clocks B - cv-source-for — A produces CV that B consumes - modulator-for — A is a modulator suitable for B (LFO, S&H, random) - audio-source-for — A is an audio source for B (typically a VCO into a VCF) - quantizer-for — A quantizes for B - trigger-source-for — A produces triggers that B consumes - envelope-target-for — A is something B's envelope output is designed to drive Catalog: - replaces — A is the newer successor to B (Morphagene replaces Phonogene) - alternative-to — symmetric: A and B occupy similar design space with different character - expander-for — A is an expander module for the host module B Direction tag on each match: - outbound: queried module is the FROM side (role-bearer). Match is what the queried module does as R. - inbound: queried module is the TO side. Match is the R-for the queried module. - symmetric: only for alternative-to. Args: - module_id (string, required): "<manufacturer-slug>/<module-slug>" - relationship (string, optional): one of the values above. Omit for all edges. - limit (number): default 50, max 200 Returns: { "module": { id, name }, "relationship": <relationship> | null, // null when none was passed (all-edges query) "matches": [{ id, name, manufacturer, notes, source_id, direction, relationship }] } If the module is unknown, returns an error. If no relationships have been recorded in either direction, returns matches=[]. The `notes` field describes the edge in the canonical A→B direction; combined with `direction` the caller can read it correctly either way.
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  • Render a document (PDF / HTML / PPTX / DOCX) and save it to the workspace. This tool has two input pipelines — pass **exactly one** of `content_html` or `content_markdown`. # Pipeline A — `content_html` (canonical for decks, proposals, designed pages) You author full HTML+CSS. A baked-in design-system preamble ships first (`<style>` with Inter/Manrope as data-URI fonts, CSS-variable palette tokens, 8px spacing scale, and pre-styled layout helpers); your markup and any of your own `<style>` blocks land after the preamble so you can override anything. Chromium renders the assembled document into a static PDF — JavaScript is disabled and DNS is blackholed, so external font / image / script fetches will fail by configuration. Required when this pipeline is used: - `title` — human-readable, used for PDF metadata and the saved filename. - `content_html` — the `<body>` and any custom `<style>` blocks. The renderer wraps this in `<html>…</html>` and injects the preamble + a canonical `<meta charset>` + `<title>`. Do NOT emit `<script>`, `<iframe>`, `<object>`, `<embed>`, `<meta>`, `<link>`, `<base>`, `<form>`, or event handlers — the sanitizer strips them. - `output_type` — `"pdf"` or `"html"`. (`"pptx"` and `"docx"` require `content_markdown` since they need structured markdown intermediates.) Optional: - `page_preset` — `"slide_16_9"` (default for any deck), `"a4"` (default for flowing documents — used if omitted), `"letter"`, or `"none"` (you declare your own `@page` rule). - `design_tokens` — flat dict overriding the preamble's CSS variables. Whitelisted keys: `brand_primary`, `accent`, `surface_dark` (hex color), `font_display`, `font_body` (font name from ['Inter', 'Manrope', 'monospace', 'sans-serif', 'serif', 'system-ui', 'ui-monospace', 'ui-sans-serif', 'ui-serif']). - `language` — BCP-47 tag (default `"en"`). Drives `<html lang>`. ## Slide structure (`page_preset="slide_16_9"`) Each slide is `<section class="slide …">…</section>`. The base `.slide` class is what sizes it to the viewport and forces the page break — do not drop it. Composable variants (apply alongside `.slide`): - `.slide-cover` — gradient hero, big display title. - `.slide-split` — two equal columns, image + narrative. - `.slide-stats` — three-up KPI cards (use `<div class="stat">` with `.stat-value` + `.stat-label` inside). - `.slide-quote` — centered pull quote + `<cite>` attribution. Layout helpers (work in any preset): `.grid-2`, `.grid-3`, `.split`, `.stack`, `.cluster`, `.callout`, `.muted`, `.kbd`. ## Speaker notes `<aside class="notes">…text…</aside>` inside a `<section class="slide">`. The sanitizer strips them from the rendered PDF and returns them as `slide_notes[]` (parallel to slide order). Orphan notes outside any slide are dropped with a warning. ## Images Only these `src` schemes resolve: - `file:NNN` — workspace `file_id`. - `data:image/...;base64,...` — inline. - `https://<host>` where `<host>` ∈ `DOCUMENTS_MEDIA_URL_ALLOWLIST`. Other URLs are dropped and replaced with an HTML comment placeholder. # Pipeline B — `content_markdown` (invoice / contract only) Required: - `title`, `content_markdown`, `output_type`. Optional: - `theme` — `"invoice"` or `"contract"`. Triggers the corresponding exemplar styling and (for invoices) the arithmetic validator that fail-closes on missing or mismatched totals. - `language` — BCP-47 (default `"en"`). # Delivery contract (CRITICAL) After this tool returns `file_id`, deliver the file with `messages.send(attachments=[file_id], text="<short caption>")`. Embedding the file_id in a markdown link, `sandbox:` URL, or `/api/files/<id>/download` text will render as plain text on the recipient's channel — the `attachments` parameter is the only way the file actually attaches. # Exemplars INVOICE (English): # Invoice INV-{YYYYMMDD-HHMMSS} **From:** {Issuer Legal Name}, {Address}, {Tax ID} **To:** {Customer Name}, {Customer Address}, {Customer Tax ID} **Issue date:** {YYYY-MM-DD} **Due date:** {YYYY-MM-DD} | Description | Qty | Unit price | Total | |---|---:|---:|---:| | {Service 1} | 1 | 1500.00 | 1500.00 | | {Service 2} | 2 | 500.00 | 1000.00 | **Subtotal:** USD 2500.00 **Tax (20%):** USD 500.00 **Total:** USD 3000.00 **Payment:** {bank details OR crypto wallet — never both} INVOICE (Russian): # Счёт-фактура № INV-{YYYYMMDD-HHMMSS} **От:** {Юридическое название организации}, {Адрес}, ИНН {Tax ID} **Кому:** {Название клиента}, {Адрес клиента}, ИНН {Tax ID} **Дата:** {YYYY-MM-DD} **Срок оплаты:** {YYYY-MM-DD} | Описание | Кол-во | Цена | Сумма | |---|---:|---:|---:| | {Услуга 1} | 1 | 1500.00 | 1500.00 | | {Услуга 2} | 2 | 500.00 | 1000.00 | **Подытог:** USD 2500.00 **НДС (20%):** USD 500.00 **Итого:** USD 3000.00 **Реквизиты:** {банковские реквизиты ИЛИ криптокошелёк — не оба сразу} CONTRACT (English): # Service Agreement **Between:** {Provider Legal Name}, {Address} ("Provider") **And:** {Client Legal Name}, {Address} ("Client") **Effective date:** {YYYY-MM-DD} ## 1. Scope of services {Concise description of what Provider agrees to deliver.} ## 2. Term This Agreement begins on the Effective date and continues until {termination condition or end date}. ## 3. Compensation Client pays Provider {amount and currency} according to {payment schedule}. ## 4. Confidentiality Both parties agree to keep proprietary information of the other party confidential during and after the term of this Agreement. ## 5. Termination Either party may terminate with {N} days' written notice. ## 6. Governing law {Jurisdiction}. --- **Provider:** ____________________ **Client:** ____________________ {Provider signatory name} {Client signatory name} CONTRACT (Russian): # Договор оказания услуг **Между:** {Юридическое название Исполнителя}, {Адрес} ("Исполнитель") **И:** {Юридическое название Заказчика}, {Адрес} ("Заказчик") **Дата вступления в силу:** {YYYY-MM-DD} ## 1. Предмет договора {Краткое описание услуг, которые Исполнитель обязуется оказать.} ## 2. Срок действия Договор вступает в силу с указанной даты и действует до {условие прекращения или дата окончания}. ## 3. Стоимость и порядок оплаты Заказчик оплачивает услуги Исполнителя в размере {сумма и валюта} в порядке {график платежей}. ## 4. Конфиденциальность Стороны обязуются сохранять конфиденциальность сведений, полученных в ходе исполнения настоящего Договора, в течение срока его действия и после его прекращения. ## 5. Расторжение Любая из сторон вправе расторгнуть Договор, направив письменное уведомление не менее чем за {N} дней. ## 6. Применимое право {Юрисдикция}. --- **Исполнитель:** ____________________ **Заказчик:** ____________________ {ФИО подписанта Исполнителя} {ФИО подписанта Заказчика}
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  • Search the corpus for Eurorack modules matching a combination of filters. Filters compose with AND. Omit any filter to leave that dimension unrestricted. The result is sorted by module name; pagination metadata in the response envelope lets you page through long result sets. Args: - capability (string): capability id, e.g. 'envelope-generator', 'clock-source'. Run a search with NO capability filter to get the full capability taxonomy (ids + labels + counts) in _meta.taxonomy. Retired/variant slugs resolve via the capability_aliases layer (e.g. 'low-pass-gate' → 'lowpass-gate', 'quantiser' → 'quantizer'), so either form is accepted. - manufacturer (string): manufacturer id, e.g. 'make-noise', 'mutable-instruments'. - hp_min, hp_max (number): module width in HP. hp_max=10 finds modules ≤ 10 HP. - signal_type_in (string): the module accepts a jack of this signal type as input. One of audio, cv, gate, trigger, clock, mixed. signal_type_in='audio' and ='cv' both also match jacks tagged 'mixed' (the schema's value for jacks the source describes as accepting both audio and CV — e.g. Joranalogue Compare 2's signal inputs); the other values match literally. - signal_type_out (string): the module produces a jack of this signal type as output. Same 'mixed'-superset semantics as signal_type_in. - text (string): free-text match against module id, name, slug, description, and the ids/labels/descriptions of capabilities the module has (case-insensitive substring). Matches hyphenated forms like "filter-8" against the slug/id even when the display name uses a space ("Filter 8"), and is whitespace-insensitive on id/slug/name so "3x MIA" finds the module named "3xMIA". Capability-label coverage means text="multiband" finds modules tagged multiband-filter without knowing the kebab-case id, and a curated alias layer extends that to common word-form variants ("multi-output" / "multi-band" / "band-split" → multiband-filter, "low-pass" → lowpass-filter, retired ids like "voltage-controlled-filter" → vcf). Truly novel wording still requires the _meta.taxonomy overview (run a no-capability search); if you expected a hit and got 0, call report_gap so the alias can be added. - voct_tracking_range_min (number): the module has a V/Oct input whose source-stated tracking range is at least this many octaves. Use for "filters that track 5+ octaves" / "oscillators with wide V/Oct range". - voct_tracking_quality (string): the module has a V/Oct input with this tracking quality, one of 'calibrated', 'temperature-compensated', 'approximate', 'uncalibrated'. 'temperature-compensated' is the strongest claim. - voct_temperature_compensated (boolean): the module has a V/Oct input whose source explicitly states temperature compensation. Implies calibrated but separately flagged because some manuals call out only one. - audio_outputs_min (number): the module has at least this many output jacks with signal_type='audio'. Use for "multi-output filters" (≥3 audio outs surfaces LP/BP/HP-tap VCFs like Three Sisters, QPAS, A-108, Polaris) or any multi-tap audio module. Combine with capability='vcf' for the canonical multi-output-filter query. - limit (number): default 50, max 200. - offset (number): pagination offset. Returns: { "modules": [{ id, name, manufacturer, hp, capabilities: [string], description, production_status }], "total": number, // total matches (across all pages) "_meta": { "query": <args>, // Present whenever a 'capability' filter matched >=1 module (NOT gated on // total=0 — it accompanies normal results). The category-coverage // denominator, so a "best X" recommendation can self-caveat instead of // reading as "best available": // On a no-capability search: the global capability taxonomy (id, label, // description, module_count) — discover the controlled vocabulary here // instead of a separate list_capabilities call. "taxonomy": [{ "id": "lowpass-gate", "label": "Low-pass gate", "module_count": 19 }], "coverage": { "capability": "stereo-mixer", // the capability you filtered on "category_total": 9, // modules in the corpus with this capability, IGNORING your other filters "corpus_total": 388, // all modules in the corpus "note": "...best of 9 in the corpus, not best available..." // ready-to-use recommendation caveat }, // Present when the server's token-AND fallback rescued an otherwise-empty // phrase query (e.g. "pamela workout" → "Pamela's NEW Workout" via per-word // identifier match). Not an error; just signals that results came from the // relaxed pass rather than the literal phrase. "relaxed_to_tokens": true, // On total=0 (after the token-AND fallback has already been attempted), the // server adds these diagnostic hints so you can retry productively in one // turn instead of guessing variants. Each is independently optional: "would_match_without": ["capability", "text"], // filters that, if individually dropped, would yield ≥1 result — the named filter(s) cost you the match "closest_text_hits": [{ id, name, manufacturer }], // top 3 modules matching 'text' alone (other filters dropped); inspect for a close hit you filtered out by accident "did_you_mean": [{ id, name, manufacturer }], // top 3 edit-distance neighbors of 'text' when it matched nothing literally (a single-token typo like "multgrain" → multigrain); PRESENT means retry with the suggested id, ABSENT means the term is a genuine corpus gap (call report_gap) — the discriminator would_match_without can't give you "capability_suggestions": [{ id, label }], // top 3 valid capabilities matching the 'capability' arg you passed (only set when the arg wasn't a known slug or alias) — use list_capabilities for the full taxonomy "manufacturer_suggestions": [{ id, name }], // top 3 maker slugs matching the 'manufacturer' arg (only set when it wasn't a canonical slug) — the manufacturer arg is EXACT-match, so e.g. "addac" → "addac-system", "nonlinearcircuits" → "nlc"; retry with the suggested id "feedback_hint": "..." // fallback prompt to call report_gap when no other diagnostic applies } } Examples: - "What envelope generators under 8 HP exist?" → {capability: 'envelope-generator', hp_max: 8} - "What ALM modules are in the corpus?" → {manufacturer: 'alm-busy-circuits'} - "What clock sources are there?" → {signal_type_out: 'clock'} - "Modules with 'workout' in the name" → {text: 'workout'} - "Filters that track V/Oct over 5 octaves" → {capability: 'vcf', voct_tracking_range_min: 5} - "Temperature-compensated filter cores" → {voct_tracking_quality: 'temperature-compensated'} - "Multi-output filters with LP/BP/HP taps" → {capability: 'vcf', audio_outputs_min: 3} Errors: - Returns an empty modules array (and total=0) if nothing matches. Not an error — inspect _meta.would_match_without / closest_text_hits / capability_suggestions / manufacturer_suggestions to decide whether to broaden the query or call report_gap. - Invalid filter values pass through to the WHERE clause; if no module satisfies them you get total=0. After picking a hit, call get_module with the id for full details.
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  • Browse and filter exploits using STRUCTURED FILTERS ONLY (no free-text query). Use this to filter by source (github, metasploit, exploitdb, nomisec, gitlab, inthewild, vulncheck_xdb, patchapalooza, oscs, poc_monitor), language (python, ruby, etc.), LLM classification (working_poc, trojan, suspicious, scanner, stub, writeup, tool, no_code), author, min stars, code availability, CVE ID, vendor, or product. Also filter by AI analysis: attack_type (RCE, SQLi, XSS, DoS, LPE, auth_bypass, info_leak), complexity (trivial/simple/moderate/complex), reliability (reliable/unreliable/untested/theoretical), requires_auth. NOTE: To search by product name (e.g. 'OpenSSH', 'Apache'), use search_vulnerabilities instead — it has free-text query and get_vulnerability already includes exploits in the response. Examples: source='metasploit' for all Metasploit modules; attack_type='RCE' with reliability='reliable' for weaponizable RCE exploits; cve='CVE-2024-3400' for all exploits targeting a specific CVE; vendor='mitel' for all Mitel exploits.
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  • Create a frontend deployment and get an upload URL. Upload your built frontend as a zip file to the returned URL, then use manage_frontend (action: "start_deployment") to trigger the deploy. Steps: 1. Call this tool to get an upload URL 2. Upload your zip file to the URL (e.g. curl -X PUT "{uploadUrl}" -H "Content-Type: application/zip" --data-binary @frontend.zip) 3. Call manage_frontend (action: "start_deployment") with the returned deployment_id Example: Input: { app_id: "app_abc123", framework: "react-vite" } Output: { deployment_id: "uuid-1234", uploadUrl: "https://...", expiresIn: 900, maxSizeBytes: 104857600 } Prerequisites: - App must exist (use init_app to create) Free plan: 1 deployment per app. Deploying again automatically replaces the previous deployment (no need to delete first). Starter+: unlimited deployments. Framework options: - react-vite: React app built with Vite (zip the dist/ folder) - nextjs-static: Next.js static export (zip the out/ folder) - static: Plain HTML/CSS/JS - other: Any framework that produces static output SPA routing: For SPA frameworks (react-vite, nextjs-static, other), a _redirects file is auto-injected so all routes serve index.html. If your zip already includes a _redirects file, it is preserved. IMPORTANT — Zip file paths must use forward slashes (/), not backslashes (\). On Windows, zips created with built-in tools use backslashes, which causes all files to be served as text/html (breaking JS/CSS with MIME errors). On Windows use Git Bash or WSL to run: cd dist && zip -r ../frontend.zip . Common errors: - RESOURCE_NOT_FOUND: App doesn't exist Idempotency: Not idempotent — creates a new deployment each time (replaces existing on free plan). Your frontend will be deployed to https://<app-name>.butterbase.dev. Next steps: Upload your zip to the returned URL, then call manage_frontend (action: "start_deployment").
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  • Return canonical synthesis / patching techniques with role-keyed module realizations drawn from the corpus. Use this when the user asks "how do I do X?" with X being a recognisable technique (low-pass-gate plucks, pinged-filter percussion, parallel multiband processing, complex-oscillator FM, karplus-strong pluck, clocked-delay feedback, modal-resonator excitation, wavefolder harmonics, envelope-follower ducking, Maths-style function-generator omnibus). It's also the right tool when the user has a module and asks "what's this good for?" — pass filter.module_id to retrieve every technique that references the module via its role_realizations. Each technique declares role_definitions (the roles the technique uses, each with required and optional affordances) and role_realizations (concrete modules that fill each role, with the affordances they provide). The model substitutes modules from the user's rack into roles by affordance match — DO NOT treat the realization list as exhaustive or as a recipe. Args: - filter (optional): { capability?, module_id?, text? } - capability: kebab-case capability id (see search_modules _meta.taxonomy). Returns techniques whose required *or* optional capability list includes this id. - module_id: "<manufacturer>/<module-slug>". Returns techniques that have a role_realization referencing this module. - text: free-text phrase. Substring-matches against technique id/label/description AND a curated alias table (technique_aliases) — that's the right surface when a user types evocative prose like "stuttering delay", "plucked string", "source of uncertainty" that doesn't grep against any kebab-case id. Two-way alias match: long alias ("source of uncertainty") matches short query ("uncertainty"), and vice versa. - When multiple filters supplied, AND-intersects. - Omit filter entirely to list all techniques. Returns: { "techniques": [ { "id": "low-pass-gate-pluck", "label": "Low-Pass Gate Pluck", "description": "Send a short envelope...", "required_capabilities": ["lowpass-gate"], "optional_capabilities": ["envelope-generator", "function-generator"], "role_definitions": [ { "role_id": "lpg", "description": "The vactrol-based or vactrol-emulating element. Strictly required...", "required_affordances": ["lowpass-gate"], "optional_affordances": [] }, ... ], "role_realizations": [ { "role_id": "lpg", "module_id": "make-noise/optomix", "affordances_provided": ["lowpass-gate"], "notes": "Two-channel vactrol-based LPG..." }, ... ], "canonical_instance": { "rationale": "...", "lineage": [ { "position": 1, "label": "Buchla 292 (1970)", "module_id": null, "notes": "..." }, { "position": 2, "label": "Tiptop Audio Buchla 292t", "module_id": "tiptop-audio/buchla-292t" }, ... ] }, "counter_canonical_notes": [ { "claim_pushed_back_against": "Optomix is the canonical pairing with Plaits...", "evidence": "The corpus catalogs 19 LPG-capable modules..." } ], "coverage": [ { "role_id": "voice", "realizations_count": 3 }, { "role_id": "lpg", "realizations_count": 19 }, { "role_id": "env", "realizations_count": 6 }, { "role_id": "clock", "realizations_count": 2 } ] } ], "_meta": { "filter": {...}, "feedback_hint"?: string } } How to use role data: - role_realizations are CURATORIAL SAMPLES, not exhaustive lists. The coverage[].realizations_count tells you how many are documented; other modules may fill the same role. - To find modules in the user's rack that can fill a role, use find_role_realizations(technique_id, role_id, available_modules). - canonical_instance is opt-in and sparse. Most techniques don't have one; that absence is information. When present, it documents a documented historical lineage (e.g., Buchla 292 → 292t → MMG → Optomix for low-pass-gate-pluck) — NOT a prescription. - counter_canonical_notes push back on likely training-data priors. When the user invokes a canonical-sounding claim that has a counter_canonical_note, surface the pushback. Errors: - "Module not found: <id>" if filter.module_id is supplied and unknown. - Empty techniques[] with a feedback_hint when filters produce no matches — call report_gap if the user expected coverage.
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  • Bulk fuzzy name → id resolver. Pass a list of module NAMES (the way a user writes their rack — "Maths", "Plaits", "Pamela's New Workout", "Morph 4") and get back, per name, the best-matching corpus module id plus recovery affordances. This is the "import my rack" tool: resolving a 60-module inventory is ONE call here, not 60 search_modules calls. Use this the moment a user gives you a list of module names to map onto the corpus — before get_modules / draw_patch_diagram / reachable_techniques / rack_redundancy, all of which want ids. Feed the resolved best_match.id into those. For each input name it runs the same resolution search_modules uses (exact id, unique-slug recovery, module_aliases, separator-fold, token-AND, and edit-distance + multi-token fuzzy "did you mean"), then returns: - best_match: the single resolved module ({ id, name, manufacturer, hp, capabilities, production_status }), or null when nothing resolved confidently. - score: confidence 0..1 (1.0 exact id, ~0.97 unique slug / alias, ~0.9 literal name hit, ~0.72 token-AND relaxed, 0 when best_match is null). - match_kind: "id" | "slug" | "exact" | "relaxed" | "ambiguous" | "fuzzy" | "none". - did_you_mean: up to 5 fuzzy neighbours to confirm — populated when best_match is null (a near-miss like "morf 4" → joranalogue/morph-4, or "tiny time machin" → oam/tiny-time-machine). - ambiguous: up to 5 candidates when several modules tied for the match and the server declined to pick (e.g. a slug shared across manufacturers). Present them to the user; do NOT silently take the first. The server AUTO-RESOLVES a confident single match but never guesses through a genuine tie — that's the ambiguous bucket. A name with best_match=null AND empty did_you_mean/ambiguous is a real corpus gap: consider report_gap(kind="missing_module"). Args: - names (string[], required): module names or ids, up to 100. Order and duplicates are preserved in the response. Returns: { "resolutions": [ { "input": "Pamela's New Workout", "best_match": { "id": "alm-busy-circuits/pamelas-new-workout", "name": "Pamela's NEW Workout", "manufacturer": "ALM Busy Circuits", "hp": 8, "capabilities": [...], "production_status": "current" }, "score": 0.9, "match_kind": "exact", "did_you_mean": [], "ambiguous": [] }, ... ], "_meta": { "requested": 3, "resolved": 2, "feedback_hint"?: "..." } } Errors: - Throws only on a malformed call (missing/empty names array, or > 100 names). Unresolved individual names are NOT errors — they come back with best_match=null and the recovery fields.
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  • Given a rack (the module ids the user owns), return which canonical patch techniques the rack can realize, and which it is one module away from. The set-level companion to find_role_realizations: where that answers "which module fills role R in technique T?", this answers the rack owner's actual question — "given everything I own, what can I actually do, and what am I close to?". This is the right tool the moment a user gives you their modules and asks an open "what can I do / what can this rack do / what am I missing?" question — instead of guessing techniques from training priors or calling find_role_realizations technique-by-technique by hand. It runs the affordance match across the whole technique catalog for you. Returns two buckets: - reachable: every required role has a rack module that fills it. Each carries an `assignment` (role → module). `requires_shared_module: true` flags a technique only reachable by reusing one module for two roles — verify those roles can share one instance. - near_misses: all-but-one role fillable; `missing_roles` names the unfilled role(s) and the `required_affordances` you'd need. This is the acquisition signal — "you can already do X; you're one <affordance> module away from Y". Args: - rack (string[], required): module ids, e.g. ["make-noise/maths", "mutable-instruments/plaits"]. Max 64. Ids that match no module are returned in `unresolved` (with did-you-mean), not silently dropped. - limit (number): max techniques per bucket. Default 25, max 100. Stateless-rack contract: the server keeps no memory of your rack between calls — pass the COMPLETE current rack every call. A partial rack silently narrows what's reported reachable, so if a module id doesn't resolve, surface the `unresolved` did-you-mean to the user rather than proceeding on the incomplete set. Scope: reachability is role-PRESENCE based. It does NOT verify per-role instance counts (cardinality) — a technique needing two independent envelopes is judged reachable if you have one envelope source. The distinct-instance question (can one module fill two roles?) is surfaced as `requires_shared_module`, not silently assumed. For the editorial detail on a specific technique (canonical instance, counter-canonical notes, full realization list), call list_techniques; for one role's candidates, find_role_realizations. To go the other way — which of your modules are redundant / safe to sell — call rack_redundancy.
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  • Pro/Teams — second-pass adversarial certification of an architect.validate run that scored production_ready (A or B first-pass tier). ON CLIENT TIMEOUT — DO NOT RETRY THIS TOOL. **RECOVERY FIRST**: the run_id is emitted in the FIRST notifications/progress event at t=0s (BEFORE the LLM call begins). Capture it. On timeout, call `me.validation_history(run_id='<that-id>')` to fetch the persisted cert verdict; the server-side run completes independently within a 20-minute budget. This is the canonical recovery path. Use it before considering any retry. Long-running LLM call (60-180s typical; exceeds Claude Code's ~60s idle budget); MCP clients commonly close the call before the server returns. Retrying re-runs the LLM call AND burns one of your 3 cert retry-budget attempts. Mints the certified production_ready badge when both reviewers sign off; caps the run to C/emerging when the second pass surfaces a missed production_blocker. MANDATORY DOCTRINE RULE (load-bearing): the badge certifies the EXACT code that produced the validate run_id, NOT 'this codebase' in general. If you modify, fix, or iterate the code between architect.validate and architect.certify — even a single character — cert rejects with code_fingerprint_mismatch. Fixing the code voids the run. The recovery path is always: edit code → architect.validate → fresh run_id → architect.certify on the fresh run. Do NOT cert from a stale run_id after iteration; ask the user to re-validate first. WHEN TO CALL: only after architect.validate returned tier=production_ready AND the user wants the certified badge AND the code has not been touched since the validate run. NOT for tier=draft/emerging/not_applicable runs (typed rejections fire — see below). NOT idempotent across attempts: each call is one of the 3 attempts in the retry budget. BEHAVIOR: atomic one-shot single LLM call, ~60-180s server-side at high reasoning effort (small payloads finish faster; observed p99 ~250s; server-side budget is 20 min, ~5× observed max). Exceeds typical MCP-client tool-call idle budget (~60s in Claude Code), so the FIRST notifications/progress event fires at t=0 carrying the run_id. The run is atomic by contract — no in_progress lifecycle, no cancellation, no resume. Updates the persisted run's result_json (public review URL + me.validation_history(run_id=...) reflect the cert outcome). ELIGIBILITY GATE (typed rejection enum on failure): caller must own the run, tier=production_ready, less than 24h old, not already certified, within cert retry budget (max 3 attempts), no other cert call in flight for the same run_id, code fingerprint must match the validated code, AND the submitted payload must be cert-payload-complete (see Payload Completeness below — cert rejects pre-LLM with `payload_incomplete` when an imported module's surface isn't visible in the validate payload that produced this run_id). Rejection reasons (typed Literal): auth_required, paid_plan_required, run_not_found, not_run_owner, not_eligible_tier, not_agentic_component (tier=not_applicable runs), already_certified, certification_age_exceeded, retry_budget_exhausted, code_fingerprint_mismatch, code_fingerprint_missing, code_not_on_file (caller omitted `code` argument AND the 24h cert-retry hold for this run has expired or was never written. Recovery: re-run architect.certify from the same MCP session that ran architect.validate, passing the code explicitly — the server never persists code by design), payload_incomplete (submitted/validated payload imports modules whose contents aren't visible — cert refuses pre-LLM to prevent a false-precision downgrade. Recovery: re-validate with verbatim public-surface stubs for every imported module, then re-cert on the fresh run_id. Empirically validated: PR #157 iter8/iter9 cert rejections were exactly this class — code on disk was correct, the submitted payload merely omitted module visibility), cert_consensus_score_below_threshold (consensus_median<75 — consensus runs only), cert_consensus_unstable_blocker (any principle mode_stability<80% — consensus runs only), run_state_corrupt, cert_persistence_failed, cert_in_flight (a prior architect.certify call on this run_id is still running. Poll me.validation_history for the verdict; do not retry until it resolves). PAYLOAD COMPLETENESS (load-bearing for cert eligibility): the cert reviewer reads the EXACT payload that produced the validate run_id. Imported modules whose surface isn't present in the payload cause pre-LLM `payload_incomplete` refusal. Avoidance — when validating with intent to cert, bundle public-surface stubs for every imported module: `from sqlalchemy.exc import SQLAlchemyError` → include a stub class; `from app.db import models` → include a `class models:` namespace stub with the columns/methods you reference; module-level imports of `dataclass`, `Literal`, `json`, `datetime`, `timezone` MUST also be in the payload (cert correctly catches when they're omitted — code would NameError on import). 'Submit Like Production': the payload should be the code as it would actually run, not a compressed sketch. The stubs cover IMPORTED dependencies only; the certified code's own enforcement branches (approval gates, policy checks, recovery paths) must be present in full. A `# ...` placeholder reads as an ABSENT control and is graded against you, not as shorthand for one that exists. PRE-LLM REJECTION AUDIT TRAIL: when cert rejects before the LLM call (payload_incomplete, code_fingerprint_mismatch, etc.), `certification_attempts=[]` on the response — no attempt landed in the retry budget, no LLM hop occurred. The rejection envelope's `rejection_reason` + `guidance` are the actionable surface. (Audit-trail UI surfacing of pre-LLM rejections is tracked in the platform self-audit set as anomaly #5; out of scope for the cert tool itself.) INPUTS: re-send the SAME code that produced the run_id (the architect persists findings + recommendations, never code, by design — privacy-preserving). Server compares the submitted code's SHA-256 fingerprint to the stored fingerprint and rejects mismatches. Auth: Bearer <token>, Pro or Teams plan required. UK/EU data residency (Cloud Run europe-west2). Code processed transiently by OpenAI (no-training-on-API-data) and dropped; payloads JSON-escaped + delimited as inert untrusted data — prompt-injection inside code is ignored. If the cert call fails outright (provider error, persistence error), a fresh architect.certify is the recovery path; the eligibility gate enforces the 3-attempt retry budget. For long-running cert workflows the answer is to re-validate, not to make this tool stateful. OUTCOMES: certification_status ∈ {confirmed_production_ready (badge mints), downgraded_to_emerging (cert review surfaced a missed production_blocker, tier capped at C/emerging), unavailable_provider_error (LLM call failed, retry within budget)}. Cert findings + summary + attempt history surfaced on the persisted run for full inspectability.
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  • Convert HTML or Markdown to a pixel-perfect PDF. Returns JSON: { url } — a temporary download URL (valid ~1 hour). Great for generating invoices, reports, receipts, or formatted documents programmatically. Supports full HTML/CSS including tables, images (base64 or URL), and inline styles. For Markdown input, set format='markdown'. 50 sats per conversion. Use convert_file instead for converting existing files between formats (e.g., DOCX→PDF). Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='convert_html_to_pdf'.
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  • Patch diagram tool. Use when the user describes routing across multiple Eurorack corpus modules. Renders modules as boxes laid out by wire topology (matrix-shaped patches anchor on a hub; otherwise modules step left-to-right by signal-flow rank), jacks as colored ports keyed to signal type, wires as bezier curves. Inline SVG on claude.ai surfaces (web, Desktop chat, mobile); JSON elsewhere. (When to *offer* a diagram unprompted: SKILL.md §4.) **Trigger phrases:** "show me the patch", "draw what I just described", "remind me what's connected to what", "explain the routing", or any time you'd otherwise hand-draw a patch in SVG/text — use this instead of drawing. Strict gate — call only when ALL of: 1. At least 3 named corpus modules. 2. Explicit wire connections between them (user-stated or derived from a coherent description). 3. The patch is concrete — user is following a tutorial, describing their own rack, or referencing back what's connected to what. Do NOT call for: a single module, a question about one module's jacks, "what should I patch X to?" (that's a recommendation, not a graph), or hypothetical patches with unnamed placeholders ("connect a VCO to a filter"). Jack names. Corpus jack names are descriptive ("V/Oct CV input", "TRIG input", "Strumming trigger input"), not panel-text shorthand ("V/OCT", "TRIG"). The resolver accepts panel-text as a fallback when it unambiguously substring-matches one jack of the right direction (e.g. "TRIG" → "TRIG input"); successful resolutions surface as `panel_text_resolved` warnings so you can confirm. Ambiguous panel text ("OUT" on a multi-output module) errors with the candidate list. To skip the fallback entirely, call get_modules to discover the exact corpus names up front (one round trip for the whole batch). Multi-channel modules require a CH<N> prefix. Modules with per-channel jacks (Quadrax, Maths, Tangrams, Stages, Optomix, QMMG, DXG, Pamela's New Workout, Cold Mac, etc.) enumerate each channel separately — e.g. `CH1 TRIG`, `CH2 TRIG`, `CH3 TRIG`, `CH4 TRIG` on Quadrax. Bare names like "TRIG" on these modules will resolve as ambiguous; always pick a specific channel. When the patch doesn't specify which channel, default to CH1. Role per use, not per identity. A module that's a modulator in one patch can be a voice in another (Maths slow-cycle vs audio-rate cycle). Pick the role for THIS patch. The enum is intentionally coarse — four buckets, not a taxonomy — so map the edge cases: - **clock** — anything emitting timing: clocks, but also trigger/gate *sequencers* and drum sequencers (a sequencer is a clock that emits a pattern). - **modulator** — CV/envelope/LFO sources shaping another module (envelopes, LFOs, random, function generators, S&H). - **voice** — anything generating the sound being processed: oscillators, drum voices, noise, sample players, physical-modeling/granular *sources*. - **processor** — anything acting *on* an incoming signal: filters, VCAs, effects (delay/reverb), waveshapers, granular/spectral *sound-processors*, and all utilities (mixers, attenuators, mults, switches). When a module both makes and processes sound, bucket by its job in THIS patch — a granular module sculpting an external input is a processor; running free as a source it's a voice. Role is currently informational — the renderer lays out by wire topology, not by role bucket — but it's still a required field, so declare it accurately for future renderer use and so the spec reads correctly. `notes[]` is patch-level prose displayed below the diagram — settings, signal-flow narration ("PNW OUT1 firing 1/16 gates", "Channel 1 cycle mode, long rise"). Errors (descriptive — they point at fixes): - "Module not found: <id>" - "Unknown jack "<name>" on <id>. Available <inputs|outputs>: ..." — pick from the list, or call get_modules - "Ambiguous jack "<name>" on <id>: matches ..." — name a specific jack from the candidates - "Patch must have at least 3 modules" - "Wire source ... is not an output" / "Wire destination ... is not an input" - "Wire to/from unknown module ref: <ref>" - "Duplicate ref: <ref>" Cross-type wires (e.g. audio into a CV input) render normally with a warning panel below the diagram — Eurorack tolerates type mismatches by design, but warnings catch unintended ones.
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  • Publish HTML content to a live URL instantly. No account or API key required. Returns a public URL that anyone can visit. Sites expire after 24 hours unless the owner claims them. Use this when a user asks you to build, create, or deploy a website, landing page, invitation, portfolio, report, or any HTML content they want to share as a link. Supports bundled assets (CSS, JS, images) and multi-page sites (include additional .html files in assets, accessible at /{slug}/{pagename}). IMPORTANT: After publishing, always share the live URL and the claim URL with the user. The claim URL lets them take permanent ownership of the site. Store the edit_key from the response silently — do not show it to the user — you will need it if they ask you to make changes to the site later. If you lose the edit_key, ask the user to claim the site first (via the claim URL in the page footer), then provide you with their API key from the dashboard — you can use that instead.
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  • Show the current organisation plan, subscription/payment state, enabled modules, and quota usage. Use before deciding whether an agentic operation is allowed.
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  • Call this when the user asks what they can SELL, remove, downsize, or trim — "what can I sell?", "which modules are redundant?", "what's doing double duty?", "I have too many modules, what can go?", "what's not pulling its weight?". The inverse of reachable_techniques: where that adds, this prunes. Given the user's COMPLETE rack, it runs a leave-one-out over the same technique matcher reachable_techniques uses — for each module, does removing it cost any currently-reachable technique? Returns three buckets plus the overlap map: - load_bearing: removing the module drops ≥1 reachable technique → KEEP. `sole_filler_for` names the techniques it props up. - sell_candidates: removing it drops nothing AND another rack module covers the same function → the first place to look. `overlaps` names the shared function and `also_provided_by` the other providers. - utility_or_uncovered: removing it drops nothing and nothing else does its job — it fills no catalogued technique role (usually a mixer / VCA / I/O / mult) OR serves an idiom the corpus is thin on. Judge by hand; this is NOT "sellable". - overlap_map: every function ≥2 of the rack's modules provide (the "you have three reverbs" view) — the evidence behind sell_candidates. IMPORTANT — this is decision-support, not a verdict, and the limits bite here: - cardinality is NOT counted: a 2nd VCA / envelope / mult reads "redundant" though real patches use both at once. Overrule the tool on utilities. - only the curated catalog is seen: a module serving an under-covered genre looks redundant when it isn't. - two modules covering the same role are BOTH flagged — you can usually drop only one. - it cannot weigh sonic character, ergonomics, or sentiment. Trust it most for specialized overlap (e.g. several reverbs); present results as candidates to weigh, never "sell these". Pass the COMPLETE rack — the server is stateless and a partial rack distorts the analysis. Args: - rack (string[], required): module ids, e.g. ["make-noise/maths", "intellijel/quad-vca"]. Max 64. Unknown ids are returned in `unresolved` (with did-you-mean), not silently dropped.
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