"Design Architecture of Ontology-based AI-PHM Using Life Acceleration Algorithms" matching MCP tools:

• assess_ai_initiativeA

  aibvf-mcpA

  The front door for one AI investment decision. CALL THIS FIRST when the user describes an AI idea in ordinary language or asks whether it should proceed. It resolves industry, revenue, business function, AI tier and organisational readiness, then returns the next missing question or an Accelerate, Fix or Stop verdict. Use work_architecture to test whether the end-to-end workflow, affected roles, human decision rights and performance measures have been redesigned. A stated gap or missing work architecture evidence blocks Accelerate and stays visible in the audit trail. Pillar scores and work architecture evidence remain optional inputs, but unresolved values are never guessed and cannot unlock Accelerate. Use score_initiative when the canonical fields are already known, score_portfolio for several initiatives, and diagnose_process for measured waste in a running process. Pure deterministic calculation, no network, auth or side effects.

  ConnectorNo auth

• designesy_readiness_scoreA

  DesignesyA

  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.

  ConnectorNo auth

• get_product_detailsA

  Demand Discovery AIA

  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".

  ConnectorNo auth

• principles.listA

  AI Design BlueprintA

  List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8 experience-design laws (the design.validate rubric); 'spec' = the 8 spec-quality laws (the spec.validate rubric). Use this when you need the full inventory or want every entry in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exact slug and need full detail.

  ConnectorNo auth

• principles.getA

  AI Design BlueprintA

  Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id, title, cluster, definition, rationale, implications, and risk-if-violated (laws also carry their eponym and validator_questions). Use this when you already have the exact slug from principles.list; prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster. Returns error_payload on unknown slug for the lens.

  ConnectorNo auth

• check_dnskey_strengthA

  BlackVeil DNS & Email Security ScannerA

  Audit the cryptographic strength of DNSKEY signing algorithms used for DNSSEC. Reports which algorithm is used for DNSSEC signing keys (RSA/SHA-1, RSA/SHA-256, ECDSA P-256, Ed25519, etc.), flags deprecated algorithms (RSA/SHA-1, DSA), independent of whether the DNSSEC chain validates. Use when asked what algorithm is used for DNSSEC signing keys, or if deprecated DNSKEY algorithms are in use. Part of the scan_domain audit.

  ConnectorNo auth

• list_example_algorithmsA

  Quantum ExpectationsA

  Return the curated list of example quantum algorithms with published resource estimates (qubit count, depth/gate count, source paper URL). Useful for comparing what algorithms need vs. what hardware can deliver. Each entry carries a `provenance` field: 'published-circuit' means the figure is reproducible from the source, 'attested-estimate' means the source withholds the circuit and the figure rests on the authors' attestation, with a `provenanceNote` giving the specifics. Carry that caveat whenever you quote an attested figure; do not present it as equivalently sourced.

  ConnectorNo auth

• mio_ai_document_translatorA

  MiOffice — AI-Powered Workspace StudioC

  AI Document Translator — Translate text between 16 languages using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

  ConnectorNo auth

• principles.listA

  AI Design Blueprint DoctrineA

  List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8 experience-design laws (the design.validate rubric); 'spec' = the 8 spec-quality laws (the spec.validate rubric). Use this when you need the full inventory or want every entry in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exact slug and need full detail.

  ConnectorNo auth

• diseaseA

  MydiseaseA

  Fetch the full aggregated annotation object for a single disease id. Accepts MONDO ("MONDO:0015967"), DOID ("DOID:9351"), OMIM ("OMIM:125853") and other supported ontology ids. Returns cross-referenced data including MONDO ontology (labels, synonyms, xrefs, parents/children), gene-disease associations from DisGeNET, phenotypes from HPO, and chemical-disease relationships from CTD. Resolve a name to an id first via the "query" tool.

  ConnectorNo auth

• upload_photoA

  Dayze — Life in Days + Notable PeopleB

  Upload a photo to a Life Graph entity. Accepts image_base64 or url (one required). Re-encodes via WebP (strips EXIF/AI metadata). Person uploads also write the CRM gallery (person_photos) and avatar when set_as_avatar=true. ($0.15; API key required)

  ConnectorNo auth

• adcritter_get_design_guideA

  AdCritter for BuildersA

  Returns AdCritter design guidance for an entity at a caller-chosen guidance level - screen experiences, API integration patterns, and design philosophy. The default ('full') returns step-by-step prescription (exact layouts, colors, copy text, column orders). Request 'patterns' for balanced hints including common design patterns with softened vocabulary. Request 'facts' if you have strong visual-design instincts and just want API integration bindings (or call adcritter_get_api_reference and adcritter_get_usage_guide directly and skip this tool). Guidance is format-agnostic - it describes outcomes and integration, never prescribes frameworks or architecture. Available entities: ad, advertiser, audience, authentication, blueprint, campaign, geo, media-asset, plan, report, settings.

  ConnectorNo auth

• principles.getA

  AI Design Blueprint DoctrineA

  Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id, title, cluster, definition, rationale, implications, and risk-if-violated (laws also carry their eponym and validator_questions). Use this when you already have the exact slug from principles.list; prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster. Returns error_payload on unknown slug for the lens.

  ConnectorNo auth

• adw.adw_402A

  AlpineDataWorks Intelligence ServerB

  Returns a 0-100 US consumer-loan delinquency stress score (z-scored composite of EIA consumer-survey and utility-payment stress indicators, history to 1988) with stress_score, acceleration, percentile_rank, confidence, and methodology_version. Call when the user asks about consumer credit stress, delinquency trends, or eviction risk, or when timing collections staffing, bad-debt provisioning, or rental-portfolio exposure — acceleration leads residential eviction filings by about two months. Updates: quarterly.

  ConnectorNo auth

• diseaseA

  OpentargetsA

  "Disease profile for [EFO_N]" / "look up disease [ID]" — fetch a disease profile from Open Targets by EFO (Experimental Factor Ontology) ID. Returns name, description, therapeutic areas, ontology cross-refs. Pair with `disease_associations` to find drug targets for the disease.

  ConnectorNo auth

• mio_ai_face_swapA

  MiOffice — AI-Powered Workspace StudioC

  Face Swap — Swap faces between photos using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

  ConnectorNo auth

• mio_ai_document_summarizerA

  MiOffice — AI-Powered Workspace StudioC

  AI Document Summarizer — Summarize long documents into key points using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

  ConnectorNo auth

• mio_ai_clip_makerA

  MiOffice — AI-Powered Workspace StudioC

  AI Clip Maker — Extract the best short clips from long videos using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

  ConnectorNo auth

• embedding_similarityA

  IA-QA — 130+ QA & Dev Tools for AI AgentsA

  Compute text similarity using local algorithms (Bag of Words, TF-IDF, Character N-grams). No API key needed — runs entirely in-process. NOT real embeddings: for true semantic similarity with vector embeddings, use run_semantic_tests with mode="embeddings" and your OpenAI API key. Supports single pair or batch mode with pipe-separated pairs. Useful for RAG retrieval testing, semantic search evaluation, and text deduplication.

  ConnectorNo auth

• get_product_detailsA

  Demand Discovery AIA

  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".

  ConnectorNo auth

• termA

  Hpo ApiA

  "What does HP:[N] mean" / "look up HPO phenotype [ID]" — fetch a single Human Phenotype Ontology (HPO) term by ID. HPO is the standard ontology for clinical phenotypes used in rare-disease research. Returns label, definition, synonyms, cross-references. Example ID: HP:0001250 (Seizure).

  ConnectorNo auth