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741,519 tools. Updated 2026-11-04 05:16

"Interactive and Fun MCP Servers for Online Gaming" matching MCP tools:

  • Generate a Mermaid.js flowchart for human visual inspection only. NOT for orphan detection or programmatic analysis — use audit(mode=orphans) to find isolated memories. Output may be truncated for large domains; never infer graph properties (e.g. orphans) from a truncated result. Pass memory_id (memory ID) to see a single memory and all its direct connections. Pass domain to see the full domain graph (most-connected memories first, capped at limit, default 40 max 100). Returns JSON with mermaid, node_count, edge_count, nodes_shown, nodes_total, edges_shown, edges_total, truncated, memories([{id,label}]) and connections([{from,to,relationship}]). If client supports HTML widgets, prefer passing memories and connections to an interactive renderer rather than outputting raw mermaid. If not, output mermaid inside a ```mermaid code block. If truncated is true, note only most-connected memories are shown and nodes_total/edges_total reveal what was dropped.
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  • The merge gate for ANY AI-written output — code, documentation, reports, emails, configs: returns a binary approve/reject verdict with veto power — e.g. it rejects code calling the nonexistent stripe.Inventory API, an N+1 loop with the latency arithmetic to prove it, or a doc claiming success with no evidence. Deterministic reality gates (mock/placeholder veto, gaming and bypass detection, invented-API checks) run first and cannot be overridden; a frontier-model review (ISO/IEC 25010) then scores quality, accuracy, reliability and tech debt. In a benchmark, a frontier model reviewing alone caught reward-gaming and hallucinated APIs 0/6 times in a natural review workflow; these gates catch them deterministically on every call. Read-only: nothing is executed. Call it on every AI-generated deliverable before accepting it; use validate_plan for plans, analyze_code for an advisory report without a verdict.
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  • Show the user's estimated 1-rep-max progression for a lift over time as an interactive line chart, with filters for date range and muscle group, and an exercise picker. When the user asks about this, prefer calling this tool and rendering the interactive MCP app over describing the underlying rows in text. Returns a short text summary alongside the visual view.
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  • Show one night of sleep in detail with duration, score, stages, bedtime, wake time, awakenings, and recent-night context. Prefer this for last-night or specific-night sleep questions. When the user asks about this, prefer calling this tool and rendering the interactive MCP app over describing the underlying rows in text. Returns a short text summary alongside the visual view.
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  • Day-by-day overview of one Roadcut road trip: from, to, km and where to sleep each day, highlights, ferries, seasonal mountain passes on the way, a cost estimate, and links to the full plan and the interactive planner. A trip is identified by its slug.
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  • List MULTIPLE printers with optional filters. For details on a single known printer, call get_printer instead — do not list-then-filter. For farm-wide counts ("how many printers are doing X"), call get_farm_overview instead — do not paginate this. Use status=["online"] to only see reachable printers, status=["printing"] for ones actively printing, status=["was_printing_when_offline"] for printers that dropped mid-print, status=["idle"] for available printers ready to accept a job, status=["awaiting_bed_clear"] for printers whose last print finished but the bed has not been cleared yet (NOT print_pending, which means a queued staggered start).
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  • Evaluates UI elements for accessibility issues that automated scanners miss. COST: $0.01 USDC via x402 on Base-compatible EVM network per call. Checks beyond what axe/Lighthouse/WAVE catch at the design stage: - Touch targets below 24×24px (WCAG 2.5.8 AA hard fail) - Touch targets below 44×44px (WCAG 2.5.5 AAA recommended) - Information conveyed by color alone without a secondary indicator (WCAG 1.4.1) - Missing focus indicators on interactive elements (WCAG 2.4.7) - Focus rings thinner than 2px (WCAG 2.4.11) - Focus ring contrast below 3:1 against adjacent background (WCAG 2.4.11) - Interactive elements below the practical usability height floor Args: - elements: Array of 1–50 UI element objects - screen_name: Optional label for the evaluation report Each element requires: element_type. Provide width_px/height_px for touch target checks. Provide uses_color_only + secondary indicator flags for 1.4.1 checks. Provide is_interactive + focus_visible + focus indicator properties for focus checks. Returns: Structured report with: - Per-element scores (0–100) and specific issues - Severity levels (critical/major/minor) with WCAG references - What automated tools miss and why - Concrete fix recommendations - Overall score and verdict (pass/needs_work/fail) - Top issues sorted by severity
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  • Play Quranic ayah audio with an interactive player widget. Use this when: the user asks to play/listen to ayahs. RECITER HANDLING: If the user names a specific reciter (e.g. 'Husary', 'Minshawi', 'Al-Afasy', 'Abdul Basit'), ALWAYS call lookup_reciters first to resolve the exact reciter_id — do not guess the ID. Guessed IDs routinely point at the wrong reciter. If the user doesn't specify a reciter, omit reciter_id entirely so default_reciter_id applies. Use ayah keys in 'surah:ayah' format (for example '1:1'). In each query, reciter_id is optional and defaults to default_reciter_id if omitted. Limits: max 50 queries and max 200 total ayahs per request.
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  • Visualize a trained model's backtest — a cumulative-return chart + trade log + stats. Use after `one_shot` / `list_models` with the model's `stem` to SHOW the user how it traded (the "is it actually any good" view). In ChatGPT this renders an interactive widget. In Claude, render an interactive **artifact** from this tool's structured output: a line chart of the cumulative return plus a table of the trades. Args: stem: The model stem (e.g. "14_EURUSD_15min_Model_24") from `list_models` / `one_shot`. Returns: dict with: ok, stem, symbol, timeframe, stats {ret, wr, pf, n, mdd, sharpe}, and trades [{type, entry_time, exit_time, entry_price, exit_price, pnl, pnl_pct, exit_reason, period}] (most recent ~200). exit_reason is one of TP / SL / close_only / signal / end. ret/mdd/wr are fractions; pnl_pct is percent.
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  • Scan a QuickBooks Online "Journal Entries" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Round numbers are statistically rare in real bookkeeping and frequently indicate estimates, plugs, or fraud signals worth review. Input is raw CSV text from QBO Reports → Accountant → Journal. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes QBO data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Tier-0 subset — HelloBooks Phase 3.0 anomaly detection in the paid product additionally catches GL outliers vs entity history, vendor-history mismatches, archived-vendor activity, and AI-narrated suspicious lines (which require the live HelloBooks account).
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  • Get a Chinese-metaphysics signal on a binary prediction-market question (Polymarket/Kalshi style yes/no outcomes). Use when a user — or a trading agent — wants an UNCORRELATED, for-fun read on a market: 'will X happen by date Y'. Returns a lean (yes/no/neutral), a confidence, the 五行 reasoning from the resolution date's energy, and a mandatory disclaimer. This is ENTERTAINMENT and a falsifiable ritual — NOT financial advice. Always present it as a novelty signal, never as a recommendation to place a bet.
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  • Scan a QuickBooks Online "Journal Entries" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Round numbers are statistically rare in real bookkeeping and frequently indicate estimates, plugs, or fraud signals worth review. Input is raw CSV text from QBO Reports → Accountant → Journal. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes QBO data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Tier-0 subset — HelloBooks Phase 3.0 anomaly detection in the paid product additionally catches GL outliers vs entity history, vendor-history mismatches, archived-vendor activity, and AI-narrated suspicious lines (which require the live HelloBooks account).
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  • Request a free Recao account for your human. This does NOT create an active account: it registers a PENDING one and emails your human an activation link; nothing works and no terms are accepted until they click it (the human accepts the terms at activation, not you). The API key in the response stays inert until then. Consent stays with the human, so calling this is a request, not a decision made for them: in an interactive session their approval of this tool call is the go-ahead; if you run autonomously, surface this step to your human instead of calling it. After activation, reconnect with header `Authorization: Bearer <key>`.
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  • Resolves a disambiguated Strong's number (dStrong) to its lexicon entry: lemma, transliteration, gloss, and - for a Greek entry only - a fuller definition (Abbott-Smith 1922, Public Domain). A Hebrew entry's definition field is always omitted: it is abridged BDB via Online Bible, which requires permission not yet obtained, so only its gloss is ever returned. Not to be confused with the get_verse/get_passage tools, which resolve a Ref to translated verse text, not a dStrong to a dictionary entry.
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  • Render a DXF drawing to a PNG image you can look at. Use this to answer visual questions (what does it look like, where is a feature) — it returns an image, not text. For structural facts and measurements, prefer describe_dxf; never measure pixels. Some chat UIs do not display the returned image to the user: for URL sources the result also includes a direct image link — show it to the user (e.g. as a markdown image) when they need to see the render. When the user wants to see or explore the drawing themselves, prefer view_dxf (interactive viewer) — if your platform gates it behind user approval, offer it and ask rather than substituting a static render.
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  • Search Rakentaja Outlet product catalog. Rakentaja Outlet (rakentajaoutlet.fi) is a Finnish online store specializing in electrical and construction supplies at outlet prices (~4000 products). All prices in EUR including 25.5% Finnish VAT. Args: query: Free-text search — matches product name, SKU, EAN code, or category name. Leave empty to browse without a search term. category_id: Filter to products in a specific category (integer ID). The full list of categories is available at https://rakentajaoutlet.fi/api/categories — this is a public REST endpoint, not an MCP tool. Combines with query if both given. in_stock_only: If True (default), only show products currently in stock (either in own warehouse or at supplier). Set to False to include out-of-stock products in results. sort: Sort order — "name" (default), "price_asc", "price_desc", or "newest". Ignored when query is given; search results are ordered by relevance instead. limit: Maximum products to return (1-50, default 10). Use a small limit for interactive queries; larger for bulk listing. page: Page number for paginated results (default 1). Combine with `limit` to page through results larger than the limit. Returns: JSON with keys: - products: list of product summaries with: - id, name, category, brand, sku, ean, unit - price_gross (incl. 25.5% VAT), price_net, currency - description (max 200 chars, description_truncated=true for longer) - available_for_order: boolean — can the customer place an order? (TRUE if in own stock OR supplier stock available) - availability_status: "in_stock" | "supplier_stock" | "out_of_stock" - estimated_delivery_min_days / _max_days: delivery estimate (or null) - in_stock, stock_quantity, supplier_in_stock, supplier_stock_quantity (raw fields — prefer available_for_order + availability_status) - product_url, image_url - total: total matching products across all pages - page: current page number - per_page: products per page (== limit) - total_pages: total pages available - disclaimer: legal notice that prices are indicative and confirmed at checkout Notes: - Prices include Finnish 25.5% VAT (price_gross) and net price (price_net) is shown for VAT-registered business buyers. - product_url is a direct link to the product page — pass this to the user for viewing or adding to cart. - Use `get_product_details(id)` for full description and stock check.
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  • Who is probing one named CVE, and how: counts, top probing addresses, networks, countries, fingerprints, sample request paths and a daily timeline. Use whenever the user names a CVE: "is CVE-2024-4577 being exploited in the wild", "who scans for CVE-2023-1389", "has anyone probed this before it was published". Do not pass a CVE id to payload_search_tool: the id is our label for a detection pattern and never appears in request text. For the list of CVEs being probed right now, use top_attackers_tool with by='cve'. Returns title, severity, actively_exploited and kev (the CISA KEV entry with date_added, or null), event and unique-address counts across both sensor types (first_contact_events and interactive_requests split them; an address both saw counts once), up to `limit` top probing addresses (1 to 25, default 25) with country, ASN and scanner (name and kind of a recognised research or vendor scanner, else null), top networks and countries, exploiter fingerprints, sample paths, a daily timeline and `interactive` (what the interactive sensors recorded of the probes). window: 24h, 7d (default), 30d or 90d, and on plans with the full history also 180d, 365d or all. observed: false with a note means we hold no detection pattern for that CVE, which is not evidence that nobody is scanning for it.
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  • Render a Markdown resume to a finished PDF using a ResumeMD template (default: classic — see list_resume_templates for all 32 ids). Returns JSON with a base64-encoded PDF and a suggested filename; decode the base64 to give the user the file. The PDF is generated in memory and never stored. For interactive editing, template switching, and color choices, send the user to resumemd.pro/editor instead.
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  • Use when the user asks about one Steam account itself - nickname, avatar, profile visibility, creation date, online status, current game - and nothing else. Returns the raw GetPlayerSummaries object plus SteamID conversions; cheapest profile tool, data no older than 48 hours, unknown profiles are fetched live from Steam. Private profiles return the public subset of fields (not an error); unresolvable ids return an error result. Do not use for bans, FACEIT or friends (steam_summary or the narrow tools).
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  • Use this tool only for a shop that is already in the Timeplex catalog but cannot be booked online yet: a search_shops result with bookable=false, or a newly joined shop whose menu is not registered yet (get_shop_services says so). It submits a booking request for that shop — Timeplex concierge staff contact the shop directly and reply to the customer in their language. Put the returned link_markdown into your reply as-is (never expose the raw URL). Do not use this tool for a shop name that search_shops could not find (shop_name_not_found), and not for generic searches with no matching results — in both cases tell the user it is not on Timeplex instead. For bookable shops use get_shop_services -> search_availability -> start_booking instead.
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  • Check whether one or more dm-drogeriemarkt products are available in one or more specific stores right now. USE WHEN: you need to know if one or more products can currently be bought in one or more particular physical stores. INPUT: one to five storeIds and one to ten DANs (dm product numbers). OUTPUT: for each requested DAN, whether it was found and a status per requested storeId - VERFUEGBAR (available, includes current stockLevel), NICHT_VERFUEGBAR (not available in this store right now), NUR_ONLINE (this product is not carried in ANY dm store, not just this one), PRODUKT_UNBEKANNT (DAN not found), or STORE_UNBEKANNT (storeId does not exist in our system). IMPORTANT: NUR_ONLINE means the product itself is never sold in physical dm stores - it will be the same result for every store. Do not check other or nearby stores for that product; tell the customer it is online-only right away. IMPORTANT: storeIds MUST come from the findNearbyStores tool - call it first to resolve the storeId(s) for a location. Never invent, guess, or otherwise make up a storeId yourself; a made-up storeId will come back as STORE_UNBEKANNT instead of a real availability answer. IMPORTANT: if a customer asks about availability for several products, pass ALL of their DANs (up to 10) into this single call. Never assume, infer, or extrapolate the availability of a product you have not included in a call and gotten a result for - not even from a similar or already-checked product, and not even for "usually available" items. When reporting back, state the result for every single product individually (e.g. one line per product) - never collapse multiple products into one summary statement such as "all of them are available". TIP: if a product's result is NUR_ONLINE, or it is NICHT_VERFUEGBAR and you already know from an earlier product lookup that it is available online, suggest buying it online instead and include a link to the product page if you have one. NOT FOR: click & collect / express pickup or same-day delivery eligibility (not covered by this tool), or repeatedly polling a store's stock over time. ERRORS: validation error if any DAN is invalid, dans is empty, more than 10 dans are given, storeIds is empty, or more than 5 storeIds are given.
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