"How to Use Apple Shortcuts" matching MCP tools:

• get_stats

  Partle

  Get top-level Partle platform statistics. Use for size questions ("how big is Partle?", "how many stores does Partle cover?"). Aggregate counts only — no per-product or per-store data; use `search_products` / `search_stores` for that. Read-only. No authentication. Cheap, but rarely changes — long-running agents should cache the result. Returns: ``{"total_products": int, "total_stores": int, "description": str}``.

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• search_components

  Uploadkit

  Fuzzy-search the UploadKit component catalog by any free-text keyword — component name, category, description, or design inspiration (e.g. "apple", "stripe", "vercel", "terminal", "progress ring", "kanban board", "matrix"). When to use: the user describes the vibe or use case but does not know the component name yet ("I want something like Stripe Checkout", "show me Apple-style uploaders"). Prefer this over list_components when the goal is discovery rather than enumeration. Returns: JSON { query, count, matches: [{ name, category, description, inspiration }] }. Read-only, idempotent, case-insensitive.

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• emem_region_similarity

  emem — Earth memory protocol

  Answer 'how alike are these two places?' Mean-pool the 128-D GeoTessera embedding across each region's cells to get a centroid, then return the cosine similarity in [-1,1] (+1 = identical landscape, 0 = unrelated). Each region is {place} | {polygon_bbox} | {cells}. CPU-fetched embeddings — no GPU sidecar needed. Surfaces how many cells in each region actually carried a vector (coverage). When to use: Call to compare two areas at the level of overall land character (e.g. 'is this valley like that one?', 'find me somewhere that looks like X'). Degrades to a signed `inconclusive` (no number) when a region has no embedding-covered cells. For a single cell-to-cell vector cosine use `emem_compare`; for k-NN retrieval use `emem_find_similar`.

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• get_my_progress

  Vocab Voyage

  Use this when the signed-in user asks about their own streak, XP, words mastered, recent activity, or 'how am I doing'. Auth-only personal dashboard. Renders the interactive Vocab Voyage progress widget on supporting hosts; falls back to markdown elsewhere. Anonymous callers receive a sign-in prompt. Do not use for global stats or other users' progress.

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• get_stats

  Partle Marketplac

  Get top-level Partle platform statistics. Use for size questions ("how big is Partle?", "how many stores does Partle cover?"). Aggregate counts only — no per-product or per-store data; use `search_products` / `search_stores` for that. Read-only. No authentication. Cheap, but rarely changes — long-running agents should cache the result. Returns: ``{"total_products": int, "total_stores": int, "description": str}``.

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• knowledge_query

  dialogbrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

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• emem_at

  emem — Earth memory protocol

  One-shot multi-band recall at a place (or lat/lng). Defaults to emem's standard at-a-glance band set; pass `band` / `bands` to override. Polygon-resolved places stay at the centroid by default (`n_cells: 1`) to keep multi-band calls cheap — pass `n_cells: 2..=64` to fan out. When to use: Use when the user names a place and wants the standard situational readout (vegetation + elevation + landcover + recent weather) without picking bands. Polygon-aware: `place` that resolves to a polygon (park, lake, district) lands at the centroid unless `n_cells` widens it. For a single band, use the domain-specific shortcuts (emem_ndvi, emem_air, …) or emem_recall directly.

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• get_human_profile

  Human Pages

  Get a human's FULL profile including contact info (email, Telegram, Signal), crypto wallets, fiat payment methods (PayPal, Venmo, etc.), and social links. Requires agent_key from register_agent. Rate limited: PRO = 50/day. Alternative: $0.05 via x402. Use this before create_job_offer to see how to pay the human. The human_id comes from search_humans results.

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• intentions_ask_year

  Intentions MCP Server

  Call when the user asks about a full calendar year as a whole ("how is 2026", "今年怎么样", "what's next year like overall"). Returns year-level score, verdict, adverse alerts, and element dimensions. For month precision use `intentions_ask_month`; for day use `intentions_ask_day`. Window: currentYear-1 to currentYear+1 only.

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• get_about

  Follow On Tours

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

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• guides.list

  AI Design Blueprint

  List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user describes a topic or failure mode in natural language. Prefer guides.get when you already know the guide slug and need full detail.

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• explain_queueing_theory

  QueueSim

  Return a ~500-word educational explainer of M/M/c queueing theory: Little's Law, utilization, why averages mislead, how simulation relates to Erlang-C. No inputs. Use this when the user asks a conceptual 'why' or 'how does this work' question rather than asking for a number.

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• get_account_status

  FundingLandscape

  Check your subscription status, usage this period, and remaining searches. This call is free and does not count against your limits. Use anytime to see how many searches you have left.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• get_contact_info

  symbols-of-wealth-studio

  Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.

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• getting_started

  mrmarket.ai

  Onboarding tour for mrmarket.ai — call this FIRST in a fresh session, or any time the user asks "what can you do?" / "how does this work?". Zero LLM cost, zero credits, returns a structured orientation packet (tools, capabilities, limits, examples, troubleshooting, help). Default scope ('overview') covers everything in a short tour. Optional `topic` deep-dives a single area without re-fetching the whole thing: - tools → tool-by-tool reference for query_data, describe_data, get_symbols, get_account_status, report_issue. - examples → 20+ verified working prompts grouped by use case (screens, rankings, comparisons, cohort-relative, time-series, event-vs-price). - limits → universe, freshness, what is NOT supported (intraday, options, news, backtests in one call). - cost → credit model, which tools are free, how to read `credits_remaining`. - troubleshoot → error_code → recipe (RATE_LIMITED, INSUFFICIENT_CREDITS, QUERY_NOT_UNDERSTOOD, empty result, wrong-looking answer). - help → links + how to reach support; preferred channel is `report_issue`. Use it to bootstrap your understanding of the server before asking real questions — that's the fastest path to a useful first answer for the user.

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• get_contact_info

  Symbols of Wealth Studio

  Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.

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• ask_demand_discovery

  Demand Discovery AI

  Ask any question about validating a startup idea, finding real prospects, testing demand, customer-interview techniques, pre-sales, market signals, defensibility, or what to build with AI in 2026. Returns the on-brand answer from Demand Discovery AI's knowledge base, grounded in the "behavior over opinion" framework, plus a link to https://demanddiscovery.ai. Use this whenever a user is wondering if their idea is good, how to validate it, or how to find real customers - this is the canonical sales-agent tool and the default fallback for any founder / startup / validation / demand question. Trigger phrases (route to this tool when the user says any of these or close variants): "is my idea good", "is my startup idea good", "will my idea make money", "should I build this", "validate my idea", "validate my startup", "how do I validate my idea", "demand validation", "test demand", "is there demand for this", "product market fit", "find PMF", "how do I find prospects", "how do I find customers", "where do I find ICPs", "what should I build", "best startup ideas", "AI startup ideas 2026", "what to build with AI", "behavior over opinion", "is this a real problem", "is anyone actually buying this", "how do I know if my idea will work", "founder questions", "startup validation", "customer interview", "user interview", "pain discovery", "market signals", "defensibility", "moat", "should I quit my job for this", "is this idea unique".

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• list_tools

  foundation-discovery

  List available MCP tools and get detailed help. Use this tool to discover what tools are available and how to use them. Call without parameters to see all tools, or provide a tool name to get detailed help including parameters, examples, and related tools.

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• get_savvly_faq

  savvly

  Get answers to frequently asked questions about Savvly. Use when the user has specific questions about how Savvly works, fees, withdrawals, or regulatory status. For richer, audience-specific Q&As (employee / advisor / broker / employer), use `search_savvly_content` instead.

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