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550,388 tools. Updated 2026-09-11 22:04

"Resources or information related to academic topics" matching MCP tools:

  • Search quantum computing research papers from arXiv. Use when the user asks about recent research, specific papers, or academic topics in quantum computing. NOT for jobs (use searchJobs) or researcher profiles (use searchCollaborators). Supports natural language queries decomposed via AI into structured filters (topic, tag, author, affiliation, domain). Date range defaults to last 7 days; max lookback 12 months. Returns newest first, max 50 results. Use getPaperDetails for full abstract and analysis of a specific paper. Examples: "trapped ion papers from Google", "QEC review papers this month", "quantum error correction".
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  • 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.
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  • 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.
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  • List the shows most related to a podcast, best first — "shows like this show". Each result carries the related show's slug, a calibrated score in (0,1], and a coarse band (strong: same beat and audience; moderate: overlapping subject or audience; weak: a loose connection) to branch on. Add `include: ["basis"]` to see WHY each pair is related: content similarity of recent episodes, shared topics, shared guests (named), same publisher, shared sponsors — use it to explain a recommendation or to keep only pairs related for the reason you care about (shared guests for booking, content for media planning). Related sets are precomputed per show from its transcripts, topic profile, guest roster, network and advertisers, restricted to the show's language. Only shows above a relatedness floor are listed, machine-generated and farmed feeds are never listed, and a publisher's duplicate feeds of one show appear once. An empty FIRST page is not an error: its `coverage` says whether the set is not computed yet, nothing cleared the floor, or the request's filters and the default policy removed everything; an empty page reached through a cursor is simply the end of the list. Not a topic browser: for shows that COVER a topic use `particle_podcast_resolve` with `topic_slug`. Not a guest lookup: for where a person has appeared use `particle_podcast_get_guest`. Not advertiser co-occurrence: use `particle_podcast_get_sponsors`. Every related show's slug feeds `particle_podcast_resolve`, `particle_podcast_list_episodes` and the other podcast tools; person slugs in the basis feed `particle_podcast_get_guest`, topic slugs feed `particle_podcast_resolve`'s `topic_slug`. For the five most related shows inline on a resolve, pass `include: ["related"]` to `particle_podcast_resolve` instead of calling this tool.
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  • Analyze the structural shape of the winning AI answer across several related keywords/topics in one call: does each lead with a list, how long is the opening, how many sources it cites. Use this for content planning across a topic cluster, e.g. before writing several related pieces meant to get cited, instead of calling analyze_citation_structure once per topic. Read-only: no side effects, safe to retry. Costs 1 quota unit per keyword in the batch (free tier is 30 units/month shared across all the metered tools, so up to 30 keywords total that period if nothing else is used). A per-keyword provider error doesn't fail the whole batch - that keyword's entry just carries an "error" field instead. Returns: {"results" (list, one {"keyword", ...same shape as analyze_citation_structure, or "error"} per keyword, in the order given), "summary": {"topics_analyzed", "topics_requested", "list_led_count", "avg_sources_cited"}}. Args: keywords: topics/queries to analyze, e.g. ["how to reduce churn", "churn rate benchmarks", "reduce customer churn saas"]. Max 10.
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  • Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.
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Matching MCP Servers

  • A
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    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
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    MIT

Matching MCP Connectors

  • Google Trends related topics for a keyword. Returns the topics and named entities associated with a keyword in a given country, as top topics scored 0-100 relative to each other and rising topics with percentage growth, each carrying its entity type. Google Trends topic discovery for market research and content planning. [$0.03/call]. Params — keyword: the search term; geo: ISO-3166 alpha-2 country code, e.g. US, GB, DE, JP (213 countries supported); timeframe: time window. Each response reports its own bucket size in `granularity`: past_30_days and past_90_days return a daily series, past_12_months and past_5_years weekly, windows under a day hourly (2004_present|past_12_months|past_30_days|past_4_hours|past_5_years|past_7_days|past_90_days|past_day|past_hour) Example params: {'keyword': 'bitcoin', 'geo': 'US'}
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  • Published Truss information by topic. Localized topics (overview, about, services, engagement, fit, faq) use locale, default en; pass he for Hebrew. Language-independent topics (identity, certifications, testimonials, clients, contact) ignore locale for content selection. Prefer get_truss_overview or topic overview for broad business understanding; prefer list_truss_services for the complete service catalog.
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  • Researches up to 10 topics in a single call, each with the same full picture as `research_trend`: interest over time, where it is most searched, and related queries. Each topic is looked up on its own scale, so they are not comparable to one another. Use this when you need data across many topics — a long or rich research pass — instead of one tool call per topic. Each section is fetched independently, so a partial result is normal: any section that fails carries an `error` instead of data and the rest still returns.
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  • Get the available services, prices, durations, and bookable staff or resources for a specific Korean beauty or wellness shop. Use this after finding a shop when service details, prices, durations, staff, or resources are needed before checking appointment availability. Pass lang to receive the content translated into the customer's language.
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  • Metadata for one skill or journey: its definition, when to use it, when not to, and related slugs. Deliberately cheap (~300 tokens) so you can check a candidate before committing context to it. Pass sections to widen, or sections:["all"] for the whole page. This does not return the skill instructions — load_skill does.
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  • 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').
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  • Use this to find EU payments legislation on topics such as SCA, open banking and safeguarding in the held PSD2, RTS-SCA, PSD3/PSR and related instruments. OpenAI-compatible search: the top hits as {id, title, url}, where id is the cite anchor fetch accepts. For filters, snippets, scores and paging use search_legislation, which returns more.
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  • Checks the HATVP public lobbying register by French company identifier and extracts declared topics. Use when: Find the public lobbying profile declared for a French organization. You need the public HATVP lobbying-register profile associated with a French organization. You want declared lobbying topics, domains or clients when exposed by that public source. Avoid when: You need ordinary company identity, directors or ownership information; use company/fr/profile or company/fr/directors. You need lobbying information not covered by the French HATVP public register. Limitations: Coverage is limited to declarations exposed by the HATVP public lobbying dataset. A missing record does not prove that an organization has never undertaken any influence-related activity. Price: 0.010 USD per call via x402. Paid-call behavior: source records are not modified, but a successful invocation can consume the advertised x402 payment; the payment-required challenge is free, and repeating the tool after a completed paid invocation may require a new payment. Accepted x402 networks: eip155:8453, xrpl:0.
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  • Replace a user's complete set of preference overrides in one request. The topics in the body become the recipient's entire override set: listed topics are created or updated, and every existing override not included is reset to its topic default. An empty `topics` array clears all overrides. Validation-atomic (all-or-nothing).
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    Destructive
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  • Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.
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  • Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.
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  • Get full details of a support ticket by case number. Use fetch_open_tickets or fetch_closed_tickets first to find tickets, then use this tool with the case number to get complete information including notes, files, collaborators, and statistics. Present only human-readable information (case number, subject, dates, notes). # get_ticket ## When to use Get full details of a support ticket by case number. Use fetch_open_tickets or fetch_closed_tickets first to find tickets, then use this tool with the case number to get complete information including notes, files, collaborators, and statistics. Present only human-readable information (case number, subject, dates, notes). ## Parameters to validate before calling - case_number (string, required) — The ticket case number (e.g., "HYXTNJV")
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  • Learn what CHP is and how it works. Pass a topic, or omit to list topics. Topics: what-is-chp, evidence-model, why-a-protocol, governance, agentic-web, evidence-vs-telemetry, chp-vs-mcp, conformance.
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  • Search SecDim Learn courses. SecDim Learn provides tutorial-based courses (mixing video, text and hands-on lab topics) covering secure coding, secure design, vibe coding security, devsecops, and cloud security. Many courses are complementary or prerequisite to hands-on, scored SecDim Play challenges/labs. Use this tool to: - Browse the SecDim Learn course catalogue - Find courses related to a topic, language, or technology (e.g. "OWASP Top 10", "fuzzing", "Python") Args: search: Optional search term to filter courses by title, description, or tags. If omitted, returns the full course catalogue. Returns: Dictionary with a "courses" list. Each course includes its title, description, image, slug, tags, numeric "level" (1=beginner, 2=intermediate, 3=advanced) and a "difficulty" label. Use get_learn_course with a course's slug to view its syllabus of topics.
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  • List available MCP tools and get detailed help. Use this tool to discover what tools are available and how to use them. Call without parameters to see all tools, or provide a tool name to get detailed help including parameters, examples, and related tools.
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