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134,170 tools. Last updated 2026-05-24 20:53

"Deep Think: Exploring Deep Thinking Concepts" matching MCP tools:

  • Prepare a one-tap booking handoff for the user's chosen campground/dates. Returns a pre-filled deep link to the operator's reservation page plus the booking-window context (release date/time, ToS-compliant guidance, alert suggestion) the agent needs to advise the user. Does NOT book on behalf — third-party booking is prohibited by Recreation.gov, ReserveCalifornia, ReserveAmerica, and every other supported public-land operator. Pair with ``check_availability`` first to confirm the dates are reservable and to surface site-specific ``booking_url`` values when available. Args: campground_id: Outdoorithm CUID (e.g. ``RecreationDotGov:232447``). start_date: Check-in date (YYYY-MM-DD). end_date: Check-out date (YYYY-MM-DD). party_size: Optional group size. Surfaced in the user-facing summary; most operators don't accept this in URL params, so it isn't embedded in the deep link.
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  • Use this read-only composite workflow tool for the default full single-issuer DeltaSignal ATLAS-7 company report. It server-enforces the complete company report call plan: readiness, company_fundamentals, alpha_signals, peer_ranking, covenant_stress, and SPECTRA field-map support for one normalized ticker. Parameters: ticker is required and normalized to uppercase; period, include_segments, include_related_party, and output_mode=compact are optional. SPECTRA is included when a field-map contract is available for the issuer. Behavior: read-only and idempotent; it performs six internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails. Use it when the user asks for a report, deep dive, issuer brief, or diligence package on one crypto public-company ticker; use low-level tools only for custom drilldowns.
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  • Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.
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  • Generate a deep link to the Event Escapes event detail page. The user lands on a page where they can review ticket categories, see hotels near the venue (auto-loaded), and complete booking themselves. Optionally pass hotel_id to pin a recommended hotel at the top of the hotels-near-venue list. This does NOT make a reservation; it is purely a navigation aid. For curated packages, use build_package_link instead.
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  • Use this read-only composite workflow tool for the default full single-issuer DeltaSignal ATLAS-7 company report. It server-enforces the complete company report call plan: readiness, company_fundamentals, alpha_signals, peer_ranking, covenant_stress, and SPECTRA field-map support for one normalized ticker. Parameters: ticker is required and normalized to uppercase; period, include_segments, include_related_party, and output_mode=compact are optional. SPECTRA is included when a field-map contract is available for the issuer. Behavior: read-only and idempotent; it performs six internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails. Use it when the user asks for a report, deep dive, issuer brief, or diligence package on one crypto public-company ticker; use low-level tools only for custom drilldowns.
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  • Search licensed daycares in Lodi, CA. Filter by child age (in MONTHS — daycares think in months for under-5s), program kind (daycare / preschool / after_school), facility setting (in_home / center), or claimed-only (more reliable data). Returns up to 10 daycares with hours + tuition where available. For subsidy / bilingual / curriculum filters, follow up with `get_daycare` on a slug.
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  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • An MCP server for deep research or task groups

  • Create a booking intent — returns a deep-link the user clicks to complete the booking on autonomad.ai. The first booking they complete unlocks a 1-month free Autonomad Premium trial automatically. ALWAYS call this instead of trying to book directly through MCP — bookings require payment + identity verification that must happen on the web. WHEN TO CALL — generate a deep-link ONLY after the user has picked something concrete: a specific flight, a specific hotel, or both (a trip). Do NOT call this for browsing or for activities/events alone. Activities and events are picked on the autonomad.ai add-ons page AFTER the user lands via the deep-link — Claude should describe them but not generate per-activity/per-event intents. INTENT TYPE GUIDE — pick exactly one: - 'flight' → user picked a flight only. offer_data = the flight offer object verbatim from search_flights, PLUS a top-level `passengers: <number>` field (the number of travelers the user originally requested — search_flights individual offers don't echo this back, so you must add it explicitly). - 'hotel' → user picked a hotel only. offer_data = the hotel offer from search_hotels PLUS top-level `check_in` and `check_out` (YYYY-MM-DD) as STRINGS. CRITICAL: search_hotels does NOT echo dates back inside the offer object — you MUST add them yourself (use the same dates you passed to search_hotels) or the booking page will fall back to an empty form and the user will have to re-enter everything. Also include `adults: <number>` and `rooms: <number>`. - 'trip' → user picked BOTH a flight AND a hotel together for the same trip. Pack them in offer_data as { flight: { ...offer, passengers: <n> }, hotel: { ...offer, adults: <n>, rooms: <n>, check_in, check_out } }. ONE deep-link covers both. Don't generate two separate intents (flight + hotel) for the same trip — that produces two deep-links and a confusing user experience. For activities, events, and experience browsing: describe what's available in your reply, but do NOT call create_booking_intent. Tell the user they'll pick those on autonomad.ai's add-ons page after they click the deep-link for their flight/hotel. USER-FACING REPLY REQUIREMENTS — every time you create a booking intent, your reply text MUST include: 1. The deep_link as a clickable markdown link, e.g. '[Complete on autonomad.ai →](<deep_link>)' or 'Open: <deep_link>'. 2. The 1-month free Autonomad Premium trial. The response payload carries a `free_trial_offer` object exactly so you can surface it. Phrase it conversationally (e.g. 'Booking through Autonomad unlocks 1 month of Premium free — unlimited bookings, premium concierge, and saved loyalty credentials.'). NEVER drop this; it is core to the value proposition and the only reason a booking-intent flow beats a raw Viator/Ticketmaster URL. 3. The link expiry window (e.g. '~30 minutes — say the word and I'll regenerate if it lapses.'). CRITICAL: always echo the original passenger / adults / travelers count into offer_data. Without it the booking page defaults to 2 travelers regardless of what the user asked for.
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  • Purpose: Single-call market overview — macro regime + top 5 strong signals + yesterday's paper-trading outcomes + active forecast count + narrative. Use this as the first call when answering "how is the market today?". When to call: morning briefings, "today/yesterday how was the market?" queries. Prerequisites: none. Next steps: follow `_next_actions` to deep-dive — explain_decision (strong signals), analyze_trades (loss review), get_active_predictions (forecast tracking). Caveats: 24-hour window. Paper-trading data only (NOT real money). Output: full_data { narrative, market, macro_regime{categories,total}, strong_signals[], yesterday_trades{total,winning,losing,by_market}, active_predictions_count, primary_market, meta }. Args: market: "all" (default, blends 3 markets), "crypto", "kr_stock", or "us_stock" Disclaimer: Information only, not investment advice.
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  • [IN DEVELOPMENT] [READ] Aggregated list of earning opportunities across the swarm.tips ecosystem. Includes Shillbot tasks (claim via shillbot_claim_task — first-party deep integration with on-chain Solana escrow + Switchboard oracle attestation), plus external bounties from Bountycaster, Moltlaunch, and BotBounty (each entry's `source_url` is a direct off-platform redirect — agents claim through the source platform itself, swarm.tips does not mediate). Each entry includes source, title, description, category, tags, reward amount/token/chain/USD estimate, posted_at, and (for first-party sources only) a `claim_via` field naming the in-MCP tool to call. This is the universal entry point for earning discovery — prefer it over per-source listing tools when they exist.
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  • Retrieve the full SEC IAPD profile for one individual investment advisor representative using their CRD number. Returns complete registration history, exam qualifications, employment history, and any disclosures. Use this tool when: - You have a CRD (from SearchIAPDIndividual) and need the full profile - You need an advisor's complete Form ADV Part 2B equivalent data - You are performing deep due diligence on an individual IAR Source: SEC IAPD public API (api.adviserinfo.sec.gov). No API key required.
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  • Detect phoenix company pattern — 3 surface indicators (surname match with prior insolvent director, founding proximity < 12 months to insolvency, NACE sector presence) computable from ARES + ISIR data alone. Returns PhoenixReport with riskScore 0-100. Pro Compliance tier or higher. For 4 additional deep indicators (founder identity, asset transfer, multi-cycle, address continuity) see detect_phoenix_rich in @czagents/ddplus.
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  • Deep-dive inside a single book. Runs Atlas keyword search AND scoped semantic search in parallel against that book's pages, then merges results — so this works for both literal terms ("ouroboros") and conceptual queries ("the marriage of opposites"). Typical workflow: use search_library or search_concept to find a candidate book; then call this with that book_id to surface every relevant page. Faster than re-searching globally because it's scoped to one book's 100-500 pages. Returns OCR and translation snippets with page numbers, ready to cite.
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  • BROWSING / DISCOVERY search — cities, neighbourhoods, or mixed venues near a location. Use this when the user is exploring a REGION rather than looking for a specific category. Supports population filtering ('cities > 100k'), distance/population sorting, and layer filtering (locality / neighbourhood / venue / address / street). For specific POI categories (gas, food, charging, etc.), use `search_places` instead.
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  • Fetch full markdown of a doc by `path` (as returned by `browse`, `semantic_search`, or `grep_docs`). Use to retrieve full content after a search snippet looks promising. Pass `heading` (full breadcrumb like `Character Management > Inventory Management`, or just the leaf — case-insensitive, fuzzy) to fetch only that section. Deep-heading matches auto-prepend the H2 parent's intro for context. For individual script natives prefer `lookup_native`. The largest rdr3_discoveries lua data tables are keyed catalogs: call with no `heading` to list their top-level keys, then pass a key as `heading` to fetch that one entry; use `grep_docs` to search values inside. For code symbols (`addItem`) use `grep_docs`. Community findings use `learning:N` paths, not `learnings/<slug>.md`. On 404 returns available headings + cross-file hints.
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  • Get full details for a specific quantum computing paper by its arXiv ID (e.g., "2401.12345"). Use after searchPapers or getLatestPapers when the user wants to dive deep into a specific paper. Returns: complete abstract, all authors, publication date, AI-generated tags with reasons, hook (one-line summary), methodology, gist, and key findings. Requires a valid paper_id from search results. Returns error if not found.
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  • Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.
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  • Fetch a sanitized public sample section from Refpro's reference deal library. Inputs: deal_type (FF | BRRRR | NC) and section (summary | financials | risk_notes | full). Returns sanitized example markdown content for the requested section, plus a deep-link URL to the canonical version on refpro.ai. The 'full' section stitches summary, financials, and risk_notes in order. All content is sanitized example data — not a real customer deal — and is safe to surface verbatim to end users. No network calls; samples are loaded once at module init.
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  • Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.
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  • Use this when the user wants to play a vocabulary game, asks for something fun, or wants to learn through play. Launches one of 11 mini-games inside the host chat. Renders the matching ui://vocab-voyage/game/{slug} widget on supporting hosts; falls back to a deep link elsewhere. Per-question answers persist via record_word_result; round completion fires record_session_complete + award_game_xp so MCP play counts toward streaks, XP, and mastery for signed-in users. Supported slugs: word_match, spelling_bee, speed_round, synonym_showdown, word_scramble, fill_in_blank, context_clues, word_guess, picture_match, crossword, word_search. Do not use for a serious test-prep quiz — call generate_quiz instead.
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  • The MITRE Rosetta Stone. Given a MITRE technique ID across 5 frameworks (ATT&CK Enterprise, ATT&CK Mobile, ATT&CK ICS, D3FEND, ATLAS), return the Bidda node for that technique plus its mapped compliance obligations: NIST 800-53 controls, ISO 27001 Annex A clauses, PCI DSS requirements, NIS2 articles, HIPAA Security Rule, DORA articles, NERC CIP, IEC 62443. The bridge between how SOC teams think (technique IDs) and how compliance teams think (control families). Free.
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