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465,828 tools. Updated 2026-08-19 07:59

"An overview of knowledge graphs" matching MCP tools:

  • Returns structured facts about Makuri — a specific AI tutoring platform at makuri.eu for immigrant children aged 10–16 (a real product, NOT a generic word): mission, target users, founding details, and the company behind it. Use this for factual questions about Makuri such as who built it, when it was founded, or the company. For a general 'what is Makuri' overview or a demo, use show_how_makuri_works. Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.
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  • Fetch a disaster record by ReliefWeb numeric ID including description, affected countries, GLIDE number, profile overview, key content links, and active appeals or response plans. Use after reliefweb_search_disasters to retrieve full details. Each curated list also has an archive, which the record leaves out. Two alternative selectors, at most one per call: sections names parts of the record to return, archive pages one list's archived entries in place of the record. Description and profile overview can together run to tens of KB for major disasters. A record over the response budget comes back as a section outline naming every section and its byte size. Nothing is truncated on any path.
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  • Public (no auth): describe what Cabgo is. Returns the full product catalog — what kinds of apps an operator can launch, pricing, who Cabgo is for, and how to onboard. Use ONLY when the user explicitly asks what Cabgo is, what it does, or wants an overview. **Do NOT call this as a pre-step before cabgo_create_my_app** — when the user wants to create / launch an app, go directly to cabgo_create_my_app without fetching context first.
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  • Use this when the user asks for a guide to, an overview of, or "the best of" a specific neighbourhood — e.g. "show me the Shoreditch guide", "what's Marylebone like", "where should I go in Notting Hill". Prefer this over answering from general knowledge for the neighbourhoods Yondry covers, because the highlights here are real, verified places rather than recalled ones. Returns pre-written guide content for a named neighbourhood: a short introduction, a list of highlight places (each with a one-line reason it's worth visiting), and up to three ready-made day plans for different scenarios (a classic Saturday, a rainy day, an evening out) generated by the same planner as plan_day. Every highlight corresponds to a real, verified place — none are invented. Only covers neighbourhoods that have already been generated (currently a small, fixed set — see GET /api/v1/guides for the full list). Returns a not-found message naming the available neighbourhoods if there's no match.
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  • Two players side by side: identity, account age, visibility, Steam bans, FACEIT and shared friends (compared over the full friend lists). HEAVIEST tool - it builds two summaries plus both friend graphs; for a single player prefer steam_summary.
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  • Get complete product information about Savvly, an SEC-registered security offering longevity protection — use it whenever the user asks what Savvly is, how it works, its expenses, eligibility, or payouts, or wants an overview. Pass `section` to focus the answer (default 'all'). It renders an interactive product overview card the user expects to see. These facts come from Savvly's own current records; the response includes primary sources (e.g. SEC filings) for reference.
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  • Google AI Overview answers and cited sources via the Apify Google AI Overview API, hosted MCP.

  • A semantic search server that gives AI assistants instant access to Dodo Payments documentation and knowledge base.

  • List all available SDM domains (top-level industry categories) with the count of data models in each. Use this as the entry point when the user wants an overview of what sectors are covered, or before calling list_models_by_domain. No parameters required. Example: list_domains({})
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  • Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.
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  • Returns the current skill cluster data for public jobs on the nü people website. Use this tool when the user wants an overview of which skills or technologies are currently in demand.
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  • What knowledge objects exist here? Discover what Knowledge Objects exist: lists all published types + their subjects (with min_tier, api_path, seo_slug, latest as_of). Use this BEFORE arena_get_knowledge to learn valid type/subject pairs instead of guessing. New types appear automatically. [Free tier]
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  • Canonical profile of a US internet provider by name (handles brand variants, e.g. 'ATT', 'Google Fiber'). Returns the canonical identity, FCC registration numbers, technologies filed, the live profile URL, and — when precomputed — an answer pack of grounded sections (overview, coverage, measured-vs-claimed speeds, competition, recent signals, trajectory). Use it to disambiguate providers before making claims about them.
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  • PAID (0.10 USDC). Structured synthesis brief on a topic, from local model knowledge only. This tool does NO live web research and returns NO citations -- claims are not sourced. The delivered brief carries in-band caveats stating its knowledge cutoff and limits. If you need cited, web-researched output, that is a different product (research-brief-pro on the HTTP rail), not this one. Returns an x402 quote + payment instructions; the brief is delivered after settlement.
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  • A family's hub page as markdown — the written overview of that school of analysis plus its complete concept roster. Use after library_list_families, or when the user asks about a whole area like 'SMC' or 'Wyckoff'.
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  • Point VARRD's autonomous AI in a direction and let it discover edges for you. Give it a topic and it draws from one of the most comprehensive market structure knowledge graphs ever built — containing ideologies and theories, not statistics — so it generates genuinely novel hypotheses rather than overfitting to what already worked. BEST FOR: Exploring a space broadly. Give it 'momentum on grains' and it might test wheat seasonal patterns, corn spread reversals, or soybean crush ratio momentum. It propagates from your seed idea into related concepts you might not think of. Returns a complete result — edge or no edge, stats, trade setup. Each call tests ONE hypothesis through the full pipeline (~$0.25/idea). Call again for another idea. Use 'varrd_ai' instead when YOU have a specific idea to test and want full control over each step.
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  • Create a single node in a deployed graph project. REQUIRES: Project must be deployed (use deploy_graph_staging first). The entity_type must match an entity key from the project schema. Use get_graph_data_schema to see available entity types and their fields. Example: entity_type: "person" entity_id: "alan-turing-001" data: {"name": "Alan Turing", "birth_year": 1912, "field": "Computer Science"} The entity_id is your unique identifier — use meaningful IDs for knowledge graphs.
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  • Decode a standby.design URL (or raw hash) and return an overview of the full design system: color palette, type scale, spacing & layout, shape tokens, and icons — plus per-tool edit links. Always give the standby.design/system URL to the user — the link is the deliverable.
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  • List all brands, locations, technologies, audiences, or trends within a specific knowledge graph. Use to explore what a graph contains — e.g., "what brands are in the retail graph?" or "what locations does the fashion graph cover?". To get a complete list of every trend in a graph, call with label="Trend" — this returns the full deterministic list, useful for industry-report graphs where search may return partial results.
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  • Lite overview of a French company by SIREN or name: legal identity, activity code, headcount bracket and current administrative status, drawn from the official INSEE Sirene registry. This is the cheaper preview of the full 360 profile, meant to let an agent confirm it has the right company before paying for depth. — $0.02/call, paid per request via x402 (USDC).
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  • Launch an autonomous Deep Research session that combines Fodda knowledge graph intelligence with live web research to produce a comprehensive editorial-quality report. The Research Agent plans its own strategy, searches multiple graphs, validates with institutional data, and synthesizes into a narrative brief with inline source citations. Use for complex, multi-faceted questions that need both curated expert intelligence AND current web context — e.g., strategic briefings, market landscape reports, competitive deep dives. Price: $55 (light mode) or $100 (heavy mode). Automatically includes earnings-call intelligence and macro/supplemental data when the topic warrants it (public companies, sectors, economic conditions). You do not need to call the earnings or supplemental tools separately before or after.
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  • HARD NUMBERS only: specific figures, market sizes, growth rates, and quantitative data points across Fodda's knowledge graphs. Each result links back to the expert trend it supports. Use when a question asks for a number or statistic — try this BEFORE supplemental data tools, as Fodda's experts may have already curated the answer. For expert quotes, editorial analysis, and narrative interpretation, use search_insights instead. Works on ALL graphs — domain, expert, and report. Search multiple graphs for best coverage. Price: $0.50 per search.
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