"Buy Me A Coffee" matching MCP tools:

• show_media

  switch

  Display the user's images inline — one or many. Users speak plainly and will NOT know asset ids; never ask for one, resolve it yourself. For "show me" or "show me my last image" call with NO arguments (shows the most recent image). For "show me my last 4 images / my last 10 pictures" pass count=N (returns a clean grid, up to 12). For a specific known image pass assetId. Renders a branded SwitchApp media card with a Download action per result; do not just print URLs. (Videos are not shown here — use list_my_videos and return the newest finished video's view_url, which plays.)

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• simulate_scenario

  QueueSim

  Run one of the four preset scenarios (single, coffee, grocery, callcenter) with optional overrides. Overrides apply UNIFORMLY across open hours — e.g. setting servers=5 on 'coffee' replaces the 4/6/4 staffing pattern with a flat 5 during open hours (closed hours stay at zero). Use this for (a) faithful reproduction of a scenario's defaults, or (b) uniform scaling (everywhere it was open, use these new numbers). Do NOT use this when the user wants to keep a scheduled scenario's shape but tweak just one part — there's no per-hour override here, and collapsing a 4/6/4 pattern to 5 often isn't what the user meant. For flat what-if analysis on scheduled scenarios, prefer simulate_mmc using peak params from describe_scenario. ANTI-FABRICATION: returned numbers come from a real discrete-event simulation run. Quote them VERBATIM in your reply. Do not round, estimate, or compute derived figures from training-data recall. If the user asks a follow-up about the same scenario+overrides, re-call this tool rather than recalling numbers from earlier in the conversation.

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• plan_optimal_shopping_route

  offerhopper.ai — AI Supermarket & Drugstore Shopping Assistant for Germany

  Plans the optimal shopping trip for a given list and starting location in Germany. Answers 'where should I go to buy this list, and is the trip worth it?' — not 'what's on offer near me'. Matches each item on the list to the best current offer across German supermarkets and drug stores (REWE, Aldi, Lidl, Penny, Netto, Norma, Edeka, DM, Rossmann, Mueller), then computes the cheapest realistic route by weighing product prices against travel distance and shopping time. Returns the chosen store(s), the per-item picks with live prices, the trip's savings and a worth-it verdict, and a shareable interactive grocery list. Supports car, bicycle, and pedestrian travel modes. For corridor trips (A-to-B), supply 'end_location' to route stores along the way.

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• create_checkout

  La Luer — AI Skincare Commerce

  Create a checkout URL for one or more products. Pass variant IDs (items) and/or product URLs (product_urls). When a product URL is provided (e.g. https://laluer.com/products/mira), the tool resolves it to a variant ID automatically — no catalog import needed. Supports discount codes, cart notes, and selling plans. Do not use unless the user wants to buy — use search_products or skincare_recommend first. Returns a direct Shopify checkout link the user can click to buy.

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• list_opt_demos

  SCModeling

  List the bundled SCModeling optimization demos. Returns id + label + one-line summary for each (Tariff, Coffee Co-pack, SSO Basic). Use this before describe_opt_demo or get_opt_result to know which demo_id values are valid. All demos are precomputed sample-only fixtures — for optimization on real client data, the SCModeling desktop tool is the product.

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• find_next_available_appointments

  qasper

  Find the next available bookable appointment starts across matching local service businesses. Use this ONLY when the user explicitly asks for availability, booking, the soonest appointment, or a specific appointment time. Examples: 'book me a dentist', 'who has availability tomorrow?', 'find the soonest groomer appointment', 'get me a dermatologist next Wednesday'. Do NOT use this for generic discovery requests like 'find me a dentist in Paris' or 'show me pet groomers near me'; use search_businesses for discovery. The CALLER (you, the agent) extracts the structured search fields the same way as search_businesses, and passes the service or activity wording in serviceQuery. The response only includes businesses with direct booking support, a matching service, and at least one slot whose bookingStartPolicy and remainingCapacity allow booking. An empty result does NOT mean no matching businesses exist; it only means no directly bookable matching slots were indexed. If this returns no results, call search_businesses before responding to the user.

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• arena_subscribe_signal_alerts

  Backtesting Arena

  Notify me when this signal flips? Fires when an existing Ampel-Config's signal flips (BUY ↔ SELL). Prerequisite: the user must have created that ampel-config in the web UI (`/dashboard/ampel`) — pass its UUID here; this tool cannot create one. Optional signal_types filter narrows to BUY-only or SELL-only. For the current signal state without subscribing, call arena_get_signal_status. Creates a standing subscription; it does not return a value now — collect fired updates with arena_check_subscription_updates (polling) or receive them by webhook, and end it with arena_cancel_subscription. For the CURRENT value instead of a change notification, call the matching read tool. [API Pro tier and up — max 3 active subscriptions for Pro, 20 for Power]

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• route_order

  ensotrade

  Cheapest way to fill a crypto perp order across multiple venues, and what that saves versus using the single best venue. Merges every order-book level from Binance, Bybit, Bitget, Hyperliquid, OKX and Gate into one list ordered by FEE-ADJUSTED price and walks it until filled. Use for "how should I split this order", "what's the cheapest venue to buy $2M of SOL", "how much would routing save me". Returns the per-venue allocation, the blended price, the best single venue, and the saving in bp and USD. `coin` = ticker e.g. 'sol'. `notional_usd` = order size in USD. `side` = 'buy' or 'sell'. `venues` = optional comma-separated subset (e.g. "binance,bybit") for a desk that only has accounts on some — the saving is only real on venues you can actually trade. This is a MEASUREMENT of a live book, not a prediction: it is optimal for the static snapshot, prices move while an order works, and it assumes capital is already on each venue and ignores transfer costs. Requires an EnsoTrade Pro API key.

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• search_along_route

  MapMap

  Find places (POIs) along a route with the REAL extra travel time of stopping at each — never a straight-line guess. Provide `origin` + `destination` (a route is computed) or an existing route's `geometry_polyline6`, plus a free-text `query` ("coffee", "EV charger", "truck stop") and `max_detour_minutes` (default 10). For a category intent ("fuel", "EV charger", "coffee") pass `category` instead of relying on words alone: it takes the same vocabulary as `nearby_places` (lowercased OSM tag values such as "fuel", "cafe", "charging_station", "parking", "pharmacy"), and common colloquial phrases are normalised server-side ("petrol station" and "gas station" to fuel, "coffee" to cafe, "EV charger" to charging_station). `query` alone also promotes a pure category phrase to the same browse, so "fuel" finds fuel stations rather than places whose NAME starts "Ful"; anything else stays free-text name matching. When a browse ran, the response echoes the tokens used in `matched_categories`. Candidates near the route corridor are priced through the routing engine with your costing: detour = (origin→place) + (place→destination) − (origin→destination). Costing "auto", "truck" (with a `truck` profile the detours respect dimensional/ADR restrictions), "bicycle", "pedestrian" or "motor_scooter". Returns results sorted by detour with detour_minutes, detour_km, along_route_position (0-1) and off_route_m; at most 25 candidates are priced per call (candidate_cap).

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• purchase_book

  bookstore4agents

  Complete a paid purchase of a book. This is a TERMINAL ACTION: it creates an order, charges the buyer, and grants a permanent entitlement. Only call this when the user has EXPLICITLY requested to buy. Never call as part of browsing, price comparison, or information gathering — prices are already visible in search_books results, and free previews are available via get_book_preview. If the user says 'don't buy', 'just compare', 'just tell me the price', or similar — do NOT call this tool. If the user requests an action that requires owning a book they don't own (e.g. commenting on an unowned book), do NOT silently purchase it on their behalf. Instead, tell the user the purchase requirement and ask them to confirm. Spending money is never an inferred default.

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• list_scenarios

  QueueSim

  List the four pre-built QueueSim scenarios. Returns key, title, and one-line description for each (Single Server, Coffee Shop, Grocery Checkout, Call Center). Call this when the user's problem matches one of the preset shapes — use describe_scenario for more detail and simulate_scenario to run one.

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• create_checkout

  SearchShop AI

  Create a checkout URL for one or more products. Pass variant IDs (items) and/or product URLs (product_urls). When a product URL is provided (e.g. https://laluer.com/products/mira), the tool resolves it to a variant ID automatically — no catalog import needed. Supports discount codes, cart notes, and selling plans. Do not use unless the user wants to buy — use search_products or skincare_recommend first. Returns a direct Shopify checkout link the user can click to buy.

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• ask_inspector

  ground-motion

  FREE follow-up Q&A with the SibFly Inspector about a report you ALREADY BOUGHT (buy via check_ground_motion first). Ask what the numbers mean for foundations, staleness, seasonal swings, etc. It answers only from the report's numbers (never invents), and won't give buy/walk-away advice. Per-account message allowance applies.

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• zambo_watch

  Zambo AI Tools

  Set a persistent async watcher — Zambo monitors any condition in the background and sends a Telegram alert when it fires. This is the ONLY MCP tool that works while you sleep. Claude sets the watch and moves on — you get pinged when it happens. Examples: 'watch ETH and alert me when it hits $3000', 'alert me when Anthropic releases a new model', 'watch my competitor site and ping me when their pricing changes', 'notify me when Bitcoin dominance drops below 50%'. Checks every 30 minutes via live web search + AI condition evaluation. Requires notify_telegram (Telegram username like @yourname or chat ID) or notify_email. Use zambo_watch when the user says: watch, monitor, alert me when, ping me when, notify me when, keep an eye on. When to use: call zambo_watch when the user's request matches this capability. When not to use: do not call it for unrelated work, missing required inputs, or when a safer read-only route is more appropriate.

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• snipe_safety

  x402-services

  Full rug/honeypot audit for a token: honeypot detection, buy/sell tax, source verification, mint/pause/blacklist/hidden-owner privileges, proxy check, holder & LP counts, plus a 0-100 risk score and plain-English verdict (AVOID / HIGH RISK / CAUTION / LOOKS OK). Send { address, chain? }. The must-have pre-buy safety gate for any trading agent. [x402 paid tool — price $0.005; POST /api/snipe/safety]

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• list_categories

  pifini

  Discover valid category values for search_places. Pifini's places directory uses Overture Maps' taxonomy — over 1,000 specific values like caribbean_restaurant, church_cathedral, landmark_and_historical_building — rather than broad buckets, so guessing a category string will usually miss. Call this first with a rough query (e.g. 'coffee' or 'beach') to find the exact value, then pass it to search_places' category parameter.

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• surprise_me

  agentcard

  Buy the user something totally unexpected and very silly/stupid-fun under a small dollar cap (default $10, hard max $25). Great when the user cannot decide what to order (from DoorDash etc.) or just wants a fun surprise. It kicks off a shopping conversation that FIRST brainstorms deliberately stupid ideas, picks ONE genuinely unexpected item, builds the cart, and shows the item + exact total. It NEVER checks out by itself: the reply includes a conversation_id — relay the user's explicit confirmation ("yes, place it") through the `buy` tool on that SAME conversation_id, exactly like a normal order. Each surprise_me call starts a fresh surprise; use `buy` for all follow-ups (answers, tweaks, the confirmation).

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• request_table_seat

  hovhannes.io

  Ask for one of the five guest seats at a Yerevan Product Coffee table. Call list_upcoming_tables first and pass one of its exact `startsAt` values. This sends a real request to a real person, so it takes two calls: call it once to see exactly what would be sent, show that to the person it is about, then call it again with the same values and confirm: true. A request is not a booking — Hovhannes reads each one himself and replies within 3–5 days, and no seat is held until he does.

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• cancel

  discovery

  <tool_description> Cancel a media buy campaign. This is a terminal state — cannot be reactivated. </tool_description> <when_to_use> When an advertiser wants to permanently stop a campaign. Cannot be undone. Use pause for temporary stops. </when_to_use> <combination_hints> cancel is terminal. For temporary suspension use pause instead. Remaining budget is released. </combination_hints> <output_format> Updated media buy with cancelled status. </output_format>

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• get_opt_result

  SCModeling

  Get the precomputed result for one scenario of an optimization demo. Returns the verbatim engine output JSON (AMOS for tariff/coffee, SSO output for sso-basic) including the optimal sourcing/production/transport decisions, costs, and any open/close facility variables. ANTI-FABRICATION: every numeric result is verbatim from the optimization engine that ran offline — quote them in your reply, do not round or recompute. Call describe_opt_demo first to learn valid scenario_key formats for each demo.

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