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306,627 tools. Last updated 2026-07-25 16:35

"Deep Research on MCP (Master Control Program or Related Topic)" matching MCP tools:

  • Retrieve reference documentation for the Zaira Guide API and MCP server on demand. Topics: - getting_started — how to connect via MCP or REST, first queries - endpoints — full REST endpoint reference with parameters - mcp_tools — MCP tool reference with when-to-use guidance and a routing matrix - schema — the tool entry schema - errors — error taxonomy for REST (RFC 9457) and MCP (JSON-RPC) Call with no topic to get an index of available topics. Returns: the requested topic as a Markdown-KV block. With no topic, returns an index listing all available topics with short descriptions; call again with the relevant topic for the full content. Examples (topic selection): - "How do I call the REST API?" → {topic: "getting_started"} - "What parameters does /tools accept?" → {topic: "endpoints"} - "What fields are in a tool entry?" → {topic: "schema"} - "What error shapes do I handle, and what are the recovery steps?" → {topic: "errors"} - "Which MCP tool fits my task?" → {topic: "mcp_tools"} Edge cases: - No topic argument is valid — you get the index. This is the deferred-loading path; don't load every topic at once. - Topic must match the enum exactly (lowercase, underscore). "getting-started" with a hyphen is rejected as an unknown parameter. Risk: read-only, closed-world, idempotent — no state change possible.
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  • Search Quantustik for S&P 500 tickers by symbol or company name. Paired with fetch — this is the two-tool "search"/"fetch" convention ChatGPT connectors and deep-research clients expect from an MCP server: call search first to get lightweight hits, then fetch(id) on the one(s) worth reading in full. Args: query: Ticker symbol (e.g. "NVDA") or company-name substring (e.g. "nvidia", "apple"). Case-insensitive. Returns a dict with a `results` list of up to 10 {id, title, url} objects — id is the ticker symbol, ranked exact-symbol match first, then company-name/ticker prefix, then substring. Empty query or no scan data returns an empty list, never an error.
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  • Generate a one-click signed PriceTik checkout URL for a hotel stay. Stay-based form (preferred for agents): pass providerPropertyId + checkIn/checkOut + guests/rooms (+ optional roomCode) and the server resolves the best live rate itself. Or pass a rateKey from pricetik_hotel_price_check directly; it auto-refreshes near expiry or when rateType is "RECHECK". URLs are pricetik.com/go/ affiliate redirects — pass to the user's browser unchanged, never fetch server-side. On 410 RateKeyExpired, re-call pricetik_hotel_price_check for a fresh rateKey. On 422 PackagingDenied, the rate is package-only and can't be booked hotel-only. currentBest surfaces nightlyRate, totalStayCost, currency, paymentType, rateType, freeCancellation only — no margin fields. When a stored loyalty program matches the property's chain, the response carries loyaltyApplied ({ program, memberId }) and the URL is member-stamped — tell the user which program linked.
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  • Company research for AI agents $0.03: web + scrape + firmographics + domain trust in one call. Alias: /api/x402/company-research. Ed25519-attested. Use before/after people enrichment. Upsell verified company file $0.95. ?q=company or domain. [x402 paid: GET /api/x402/deep-research-json price $0.03 on Base]
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  • Report what this session controls: the master account/subaccount, whether it can trade or is read-only, and the exact on-chain authorization scope (which messages, which subaccount, and that it CANNOT withdraw/transfer). Call this first.
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  • Report what this session controls: the master account/subaccount, whether it can trade or is read-only, and the exact on-chain authorization scope (which messages, which subaccount, and that it CANNOT withdraw/transfer). Call this first.
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  • Autonomous buy-side research: diligence, earnings, SEC filings, comp sets. Source-cited real data.

  • Conduct comprehensive research projects using a virtual computer equipped with a real browser, coding tools, document creation capabilities, and more. Deep Research by Openhelm enables your agent to tackle work such as: • Market and competitor analysis • Industry and company research • Investment and acquisition due diligence • Technical and scientific investigations • Report generation with sources and evidence What makes OpenHelm the best solution for this: • Research is continuously revie

  • Brings a web session's browser window to the FRONT so the USER can take over directly — solve a CAPTCHA, complete 2FA, or make a choice the AI shouldn't. Local MCP never solves CAPTCHAs itself; this hands control to the user. Pair with web_screenshot first to show them what's on the page. After they finish, tell the agent to continue — the session keeps its state.
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  • [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields
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  • Perform comprehensive research on a topic. Decomposes your query into sub-queries, searches and reads multiple sources in parallel, then synthesizes a structured report with citations. Best for open-ended or comparative questions that need coverage from many angles. For simple factual lookups, use search instead (optionally with include_answer=true for cheap synthesis). Costs 25 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched}), sub_queries (the decomposed queries), credits_used, credits_remaining, usage (token counts). Args: query: The research question or topic topic: "general" (default) or "news" (prioritize recent news articles) freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD" max_sources: Maximum number of sources to use, 5-30 (default 20)
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  • Structured fact-check + numerical research via Perplexity Sonar Reasoning Pro (Gateway-routed). Returns synthesized answer text plus structured sources[] with direct URLs to primary sources. Use for: specific numerical claims with methodology context, fact-check against primary sources, effect sizes + confidence intervals, earnings transcripts / SEC filings / research papers. Per Phase 3.5 empirical A/B: 2-3× cheaper than sonar-pro with comparable or better quality on structured research. Real Meta IR press releases + earnings transcripts on Desk. 17 cites on Quant. NOT for: Reddit/X/community → use search_community. NOT for: broad topic landscapes → use search.
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  • Run a full brand audit on a single target with optional standard/deep discovery depth, brand aliases, and caller-supplied candidate domains. Discovers brand-related domains, looks up registrar + registrant for each candidate, and classifies each into consolidated, real registrar-sprawl shadowIt, authorized vendor dependency, indeterminate, or impersonation relationships. Gated tier-wide by monthly BRAND_AUDIT_QUOTAS (free/agent=0, developer=50, partner=200, enterprise=500, owner=unlimited).
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  • Keyword (full-text) lookup over title + body, ranked + snippet-highlighted. Use to find a page you can name or that contains an exact term/identifier/error string. Works WITHOUT an embedder (always available). Optional space_id narrows to one space. To answer a question or gather material on a topic by meaning, use `research` instead.
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  • Premium: decomposes a task intent into subgoals and maps each to OnchainAI catalog tools, surfacing gaps where no tools exist. Returns a subgoal table with covered (candidate slugs) or gap (manual research needed) status. Always paid on public POST /mcp — $0.01 USDC on Base (Axis B; HTTP 402 + PAYMENT-REQUIRED). Use free search_tools for simple lookups. On POST /mcp/okx uses the OKX package rate instead.
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  • Real-time web search via Tavily. Use for current events, fact-checking, and research. Set search_depth='advanced' for complex research queries (higher quality, higher cost). Set topic='news' for recent headlines or 'finance' for market information.
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  • Returns a 0-100 frontier-hardware research-momentum score (Semantic Scholar publication counts for quantum computing, solid-state batteries, and neuromorphic computing — 90-day windows vs. baseline, summed) with trend, z_score, per_variant_w0, and window_counts. Call when the user asks about emerging-tech R&D acceleration, quantum/battery/neuromorphic research trends, or pre-patent signals, or when timing deep-tech investment, corporate R&D strategy, or technology-scouting decisions. Updates: daily.
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  • Run master-independent safety checks on a candidate recipe. Works for ANY recipe — no dish resolution, no master SOP required. Checks poultry internal-temperature safety and scans all ingredients for the 14 EU FIC 1169/2011 Annex II allergen groups. The verdict is a deterministic function of (candidate, kb_version_hash) — no LLM involvement. Use this when verify_recipe has no matching master for the dish: the safety layer still applies to every recipe. Returns: Safety envelope: verdict (PASSED/FAILED per the zero-critical policy gate), safe flag, issues found, and the pinned kb_version_hash.
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  • Search official economic statistics by free text, e.g. 'inflation barbados' or 'government debt japan'. Returns result ids that can be passed to fetch. Designed for deep-research connectors; for richer control use get_indicator / get_series.
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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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  • Save an ordered PP2 Program Queue draft from source candidate ids. Creates or reuses candidate-backed Program Queue items, applies the requested order, and optionally replaces/prunes stale draft items when replaceDraft=true. Requires write:program_queue scope. Does not publish or mutate the live queue.
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  • Confirm your domain-control proof and upgrade your SaSame MCP Observatory listing from Observed to CLAIMED. SaSame fetches /.well-known/mcp-ready-claim.txt (or checks the DNS TXT _mcp-ready-claim.<host>) for the challenge token from claim_start; if it matches, your listing becomes owner-confirmed 'Claimed', a signed Claimed MCP-Ready certificate is re-issued, and your badge reflects it. SSRF-guarded; free.
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