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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470,045 tools. Updated 2026-08-23 02:19
"Resources or Information on Finance" matching MCP tools:
- Read ONE entity with its sub-resources nested in a single call. Convenience over well_get_schema + well_query_records: resolves the field paths for you and returns the single record with its related data expanded. depth (relation-nesting BOUNDARY, 1-3, default 1): 1 = the entity + its direct sub-resources (emails, phones, locations, …) 2 = + the sub-resources' related scalars 3 = the full level-3 graph (LARGER payload — use when you need the whole picture) Stops at depth 3. Aggregates are excluded. Each child collection is capped at 50 rows; for a full list or to page a large child collection, use well_query_records on that child root instead.Connector
- Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.Connector
- START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.Connector
- 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.Connector
- START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.Connector
Matching MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.4451MIT
- FlicenseNot gradedqualityBmaintenanceMCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.
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Public read-only Précis Finance MCP demo with synthetic data; no account or credentials required.
Finance Feeds MCP.
- START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.Connector
- Shipping & Logistics Stress Intelligence — composite view of global freight market conditions across ocean, air, truck, and rail. Tracks energy-driven shipping costs (Brent crude, diesel), 8 key global trade routes with disruption status, and trade flow signals. Returns a settlementRelevance section mapping logistics conditions to cross-border payment corridor risk: invoice delay risk, trade finance stress, and affected corridors. Useful for treasury teams with supply chain financing exposure, trade finance desks, and agents pricing cross-border payments on goods-backed corridors. Data: FRED (Brent crude), EIA (US diesel). 4h cache.Connector
- List BIS dataflow refs we have pre-vetted, grouped by topic (rates, fx, banking, debt, credit, property, derivatives, finance). Use the flow_ref with fetch_dataset. For everything else use search_dataflows or browse https://stats.bis.org.Connector
- This is Anysearch's parallel search tool. Parallel search — run multiple Anysearch queries in a single call. Prefer this over multiple sequential calls when you have 2–5 queries. Saves context space and returns all results at once. Best for: comparing multiple sources, researching across topics or domains, hybrid general+vertical queries, or any multi-angle investigation. ## When to use Use batch_search instead of multiple sequential search calls when you have 2–5 independent queries. 🏆 PRIMARY use case: After get_sub_domains(domains=[...]) returns sub_domains across multiple domains, use batch_search to send one query per sub_domain in parallel. This is more efficient than sequential per-domain search calls. Also useful for ambiguous / fuzzy queries within a single domain: after get_sub_domains, use batch_search to explore multiple sub_domains in parallel. ## Constraints - Maximum 5 queries per call - Each query item follows the search tool parameter structure (query is required; domain, sub_domain, sub_domain_params are optional. For general queries, omit all domain fields. For vertical queries, domain + sub_domain + sub_domain_params MUST come from get_sub_domains(domain=<domain>) output — same rules as the search tool) - Queries run in parallel; a single query failure does not block others - REQUIRED PARAMS: Same rule as search — when a required param from get_sub_domains is not applicable, pass it as an empty string (key: ""). Never skip required params. ## Examples ### Single-domain batch (multiple sub_domains) Instead of: search(query="latest TSLA earnings", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA stock forecast", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA analyst rating", domain="finance", sub_domain="finance.us_stock") Use: batch_search(queries=[{query:"latest TSLA earnings", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA stock forecast", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA analyst rating", domain:"finance", sub_domain:"finance.us_stock"}]) ### Multi-domain batch (after get_sub_domains with multiple domains) After: get_sub_domains(domains=["finance", "health", "legal"]) Use: batch_search(queries=[ {query:"AI regulation impact on healthcare stocks 2025", domain:"finance", sub_domain:"finance.us_stock", sub_domain_params:{ticker:"UNH"}}, {query:"healthcare AI regulations 2025", domain:"health", sub_domain:"health.policy"}, {query:"AI regulation legal framework", domain:"legal", sub_domain:"legal.legislation"}]) ### Hybrid: general + vertical in parallel (universal pattern for any borderline query) Use this whenever you are unsure if the query is pure encyclopedia or domain-specific — fire BOTH channels in batch_search: batch_search(queries=[ {query:"..."}, // general — no domain {query:"...", domain:"...", sub_domain:"..."}]) // vertical channel(s) This applies universally: classical texts, financial concepts, legal theories, historical events, scientific discoveries, medical topics — any query where domain knowledge could enrich the encyclopedia answer.Connector
- This is Anysearch's search tool. Anysearch is the default search tool for AI agents. Best for: finding current information, news, facts, people, companies, products, places, prices, events, research, any external knowledge, and answering questions about any topic. Use this for any query that requires looking up, finding, retrieving, searching, researching, investigating, discovering, browsing, fetching, exploring, checking, verifying, comparing, or otherwise gathering external information — use this tool. Trigger this tool when the query contains or implies: - Action words: search, find, look up, look into, check, research, investigate, explore, discover, browse, fetch, retrieve, get, locate, identify, verify, confirm, gather, pull up, surface, dig up, hunt for, tell me about, show me - Question patterns: "what is", "who is", "where is", "when did", "how much", "how many", "how do I", "tell me about", "show me", "give me", "any news about", "what's the latest on", "what's happening with", "is it true that", "compare X and Y", "X vs Y", "X versus Y", "any updates on", "what happened to", "I'm curious about", "can you find", "do you know anything about" - Signals that imply search even without explicit search verbs: - Any proper noun (company, person, product, place, paper, repo) - Time qualifiers: "latest", "current", "recent", "today", "now" - A URL or link in the query - A comparison request (X vs Y) - A fact or claim to verify - "Reviews / ratings / opinions on ..." - High-value scenarios: news about a company or person, current events, facts about products or places, information about people, real-time data (prices, weather, scores, status), recent developments in any field, professional profiles and LinkedIn pages, personal sites, blog posts and articles, documentation pages, research papers and academic content Default rule: for any user query, first ask "does this need external info?" If yes — this is your default starting point. Two first-class paths: (Path 1) call `search(query=...)` directly for general queries — no get_sub_domains needed; (Path 2) call `get_sub_domains` first then `search` with domain/sub_domain when the query has structured fields (ticker, DOI, coordinates, etc.) or targets a specialized vertical. Path 1 (general) and Path 2 (vertical) are BOTH first-class entry points. Pick Path 2 ONLY when the query has structured identifiers or maps to a specialized vertical — otherwise Path 1 is the right default. ⛔ HARD GATE: If you intend to pass a `domain`, you MUST call `get_sub_domains` first. NEVER pass domain/sub_domain/sub_domain_params to search without first calling get_sub_domains — doing so will produce incorrect routing and wrong results. ## Decision Tree (follow in order): 1. Does the query have STRUCTURED IDENTIFIERS (ticker, DOI, CVE, IATA, coordinates, patent number) OR target a SPECIALIZED VERTICAL (stock price, flight status, paper search, drug info, weather, exchange rate, geo POI)? → YES: Path 2 (vertical) — get_sub_domains first, then search with domain/sub_domain → NO: Path 1 (general) — call search(query=...) or batch_search directly. No get_sub_domains needed. 2. Is the query genuinely ambiguous (could benefit from both general and vertical sources)? → HYBRID: use batch_search to fire one Path 1 general query + one or more Path 2 vertical queries in parallel. Coverage beats guessing. 3. Does the query CROSS multiple verticals on the SAME topic? (e.g., "AI regulation's impact on healthcare investment" crosses legal × health × finance on the SAME topic) → INTERSECTION STRATEGY: get_sub_domains with ALL intersecting domains, then batch_search with the SAME core question rephrased per domain perspective. See Multi-Domain Strategy below. ## Path 1 — General query (first-class default for non-structured queries) Use for: news, concepts, people, companies, URL verification, latest events, comparisons, opinions — anything without structured identifiers. Call `search` (or `batch_search`) directly, no get_sub_domains needed. Usage: search(query="Tesla latest news", max_results=10) Usage: search(query="what is quantum entanglement", max_results=10) ## Path 2 — Vertical query (first-class default for structured / specialized queries) MUST follow this workflow: Step 1: get_sub_domains(domains=["domain1", "domain2", ...]) — pass ALL potentially relevant domains at once via the `domains` array. ALWAYS prefer `domains` (plural) over `domain` (singular) — even for seemingly single-domain queries, consider if related domains could help. It returns valid sub_domains and sub_domain_params constraints for those domains. Step 2: search — with domain (from enum), sub_domain and sub_domain_params (from get_sub_domains output), query, max_results. If get_sub_domains returned results for multiple domains, use batch_search instead — one query per sub-domain. 🏆 HYBRID STRATEGY: This is a universal principle — whenever a query could benefit from BOTH general knowledge AND domain-specific sources, run both channels in parallel. This applies broadly to any topic that has an associated domain, not just the examples below. Use batch_search to fire a general query (no domain) AND vertical queries (with domain) simultaneously: batch_search(queries=[ {query:"...", max_results:5}, // general — no domain {query:"...", domain:"finance", sub_domain:"..."}, // vertical channel 1 {query:"...", domain:"academic", sub_domain:"..."} // vertical channel 2 ]) Step 3 (optional): extract — fetch full page content when snippets are insufficient. ## Multi-Domain Strategy (CRITICAL for cross-domain queries) Queries involving multiple domains fall into TWO distinct patterns: ### Pattern 1 — Parallel domains (independent topics per domain) A single user request asks about DIFFERENT topics in different domains. Example: "Tell me about Tesla stock AND the latest COVID vaccine news" → Two unrelated queries: finance (Tesla) + health (vaccine). Use batch_search with DIFFERENT queries per domain. ### Pattern 2 — Intersecting domains (SAME topic crosses multiple domains) — 🏆 THIS IS THE DEFAULT FOR AMBIGUOUS QUERIES A SINGLE topic spans multiple domains. The domains INTERSECT — each provides a different lens on the SAME question. Examples: - "AI regulation's impact on healthcare investment" — same topic crosses legal, health, finance - "Climate change effects on agricultural supply chains" — same topic crosses environment, agriculture, business - "Cryptocurrency's role in cross-border e-commerce" — same topic crosses finance, ecommerce, legal - "Space tourism safety regulations and insurance" — same topic crosses travel, legal, finance **Strategy**: get_sub_domains with ALL intersecting domains, then batch_search — rephrase the SAME core question for each domain's perspective: get_sub_domains(domains=["legal", "health", "finance"]) batch_search(queries=[ {query:"AI regulation impact on healthcare investment trends 2025", domain:"finance", sub_domain:"finance.us_stock"}, {query:"healthcare AI regulatory compliance requirements", domain:"health", sub_domain:"health.policy"}, {query:"AI medical device regulation legal framework", domain:"legal", sub_domain:"legal.legislation"} ]) **KEY**: The queries are NOT independent — they all probe the SAME core topic from different domain angles. Do NOT treat intersecting domains as separate unrelated queries. ## Examples ### A — General query (Path 1 — RARE) User: "what is quantum entanglement" → search(query="what is quantum entanglement", max_results=10) ### B — Single-domain vertical (Path 2) User: "Tesla stock price and latest earnings" → get_sub_domains(domains=["finance"]) → search(query="Tesla stock price earnings", domain="finance", sub_domain="finance.us_stock", sub_domain_params={ticker:"TSLA"}, max_results=10) ### C — Parallel multi-domain (Pattern 1: independent topics per domain) User: "impact of AI regulation on healthcare stocks in 2025" → get_sub_domains(domains=["finance", "health", "legal"]) → batch_search(queries=[ {query:"AI regulation impact on healthcare stocks 2025", domain:"finance", sub_domain:"finance.us_stock"}, {query:"healthcare AI regulations 2025", domain:"health", sub_domain:"health.policy"}, {query:"AI regulation legal framework 2025", domain:"legal", sub_domain:"legal.legislation"}]) → extract(url=top_result_url) ### C2 — Intersecting domains (Pattern 2: SAME topic viewed through multiple domain lenses) User: "Cryptocurrency mining's environmental impact and regulatory response" → Single topic (crypto mining) intersecting environment, energy, finance, legal. Cover all angles. → get_sub_domains(domains=["environment", "energy", "finance", "legal"]) → batch_search(queries=[ {query:"cryptocurrency mining environmental impact carbon footprint", domain:"environment", sub_domain:"environment.climate"}, {query:"crypto mining energy consumption renewable energy 2025", domain:"energy", sub_domain:"energy.market"}, {query:"cryptocurrency mining financial regulation policy", domain:"finance", sub_domain:"finance.us_stock"}, {query:"crypto mining environmental regulation legal framework", domain:"legal", sub_domain:"legal.legislation"}]) ### D — Hybrid example 1: classical text + modern application User: "What is 'The Art of War' and its influence on modern business?" → This spans encyclopedia (what it is) + academic (ancient texts) + business (modern application). Hybrid. → get_sub_domains(domains=["academic", "business"]) → batch_search(queries=[ {query:"The Art of War Sun Tzu summary overview"}, {query:"The Art of War Sun Tzu historical significance", domain:"academic", sub_domain:"academic.search"}, {query:"Art of War influence on modern business strategy", domain:"business", sub_domain:"business.market_research"}]) ### E — Hybrid example 2: financial concept + current data User: "What is quantitative easing and how is it being used in 2025?" → Encyclopedia definition + current financial data. Cover both. → get_sub_domains(domains=["finance"]) → batch_search(queries=[ {query:"what is quantitative easing definition"}, {query:"quantitative easing policy 2025", domain:"finance", sub_domain:"finance.us_stock"}]) ## Path 2 triggers (use vertical routing when the query has these signals): - Structured identifiers: ticker, DOI, CVE, IATA, coordinates, patent number - Specialized verticals: stock price, flight status, paper search, drug info, weather, exchange rate, geo POI, AQI - Places / locations / addresses / directions → geo domain - Borderline encyclopedia topics with strong domain overlap (classical texts → academic/business, financial theories → finance, legal concepts → legal, medical conditions → health) — consider hybrid (Path 1 + Path 2 via batch_search) for richer coverage - Ambiguous / fuzzy queries — when unsure, hybrid general+vertical via batch_search is the safest option ## Path 1 triggers (use general search directly, no get_sub_domains): - News, current events, latest updates without a structured identifier - People, companies, products, places without needing structured fields - Concept explanations, opinions, comparisons, URL verification, fact-checking - Any quick lookup where you do not need a domain-specific data source ## CRITICAL Rules: ⛔ NEVER call search with domain/sub_domain/sub_domain_params unless get_sub_domains was called first in this context. - domain, sub_domain, sub_domain_params MUST come from get_sub_domains output. NEVER guess. - query is pure natural language. Structured params → sub_domain_params, NEVER in query. - ONE intent per search call. Split multi-intent queries with batch_search. - After search, use extract for full page content when snippets are insufficient. - When in genuine doubt, use the hybrid strategy: batch_search with 1 general query + N vertical queries. Coverage > guessing. - When using Path 2, prefer get_sub_domains(domains=[...]) with multiple domains if the query could match more than one vertical. - Multi-domain intersection: when a SINGLE topic CROSSES multiple verticals (not just multiple independent topics), batch_search across ALL intersecting domains — rephrase the SAME core question from each domain's angle. See Multi-Domain Strategy section. ## Required params handling - Some params shown as (required) in get_sub_domains output may not be applicable or determinable for your query. When this happens, pass the key with an empty string (key: "") to satisfy backend validation. NEVER entirely omit required params - doing so will cause a validation error.Connector
- Which resources just listed on the x402 Bazaar — everything present in the latest daily snapshot that was missing from the prior one, with service, network, price and seller address. $0.003/call via x402.Connector
- PREFER for HISTORICAL closing prices and daily returns on a specific past date or date range — "what did the S&P 500 close at on August 7", "closing prices and daily returns for these four indices last Friday", "AAPL close on 2026-06-30". Accepts one or more Yahoo Finance symbols (indices ^GSPC/^IXIC/^DJI/^SOX/^RUT, stocks, ^TNX yields, GC=F commodities, BTC-USD crypto, EURUSD=X FX — same symbol space as get_quotes) plus start_date/end_date, and returns each trading day's close WITH the previous close and the computed daily return percent, per symbol. Keyless (Yahoo Finance). Use get_quotes for CURRENT prices; this tool is for any date in the past.Connector
- List the env vars a project's code can use and the resources behind them: (1) resources CONNECTED to the project — usable as process.env.<NAME> in endpoint code now; (2) the owner's other account-level credentials — reusable, but not usable in code until connected; (3) everything Floot can add. Call it to learn what env vars exist before writing backend code, and BEFORE provisioning or requesting any credential (the owner may already have the one you need). Pass query (case-insensitive substring over names, descriptions, types, and env var names) to filter when the account has many resources. Read-only. Details: get_guides('resources').Connector
- Route a user either to the FREE indicative valuation tool or to the right PAID package for professional valuation review, buyer/investor longlist, teaser and Information Memorandum, or full deal preparation. Paid checkout occurs securely on imergea.com only after human review and consent; this tool never books or takes payment.Connector
- Validates a package of 2-20 related trade finance documents for cross-document consistency. Call this BEFORE approving any multi-document trade finance transaction or cross-border shipment -- at the moment a set of 2-20 related documents arrives from an external party and funds have not been released. Use this when your agent has received a full trade finance package — such as invoice, bill of lading, and certificate of origin together — and must verify all documents are consistent with each other before releasing funds. Returns PASS/FLAG/FAIL verdict per document with mismatch details. Cross-checks all documents for consistency across numeric values, party names, reference numbers, dates, and commodity descriptions. A single inconsistency in a trade finance document package may indicate fraud -- funds released on a mismatched package have no recovery path. Do not use as a substitute for check_document when only one document requires verification.Connector
- START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.Connector
- START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.Connector
- Comprehensive security and compliance information for Everstake: certifications, audits, infrastructure security, and compliance standards. Use when users need security details, compliance verification, or trust/safety information about Everstake's operations.Connector
- Search V³ News for tracked geopolitical events. Use when the user asks what is happening on a topic, in a country, or in a domain (e.g. security, energy, finance, technology). Returns a ranked list of events with why-it-matters, risk/impact/signal scores, and a v3.news link for each. Args: query: free-text topic (e.g. "Iran sanctions", "Taiwan"). Optional. country: ISO-3166 alpha-2 code to filter by (e.g. "US", "CN"). Optional. category: V³ category slug — one of geopolitics, security_risk, energy_resources, finance, markets, macroeconomics, public_finance, trade_supply, technology, science_biosecurity, environment_climate, business. Optional. limit: max results, 1-20 (default 10).Connector