"Information or topic related to 'context7'" matching MCP tools:

• search_content

  flevy

  Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.

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• zaira_get_docs

  Zaira Labs Guide

  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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• what_matters

  Autario Data Analytics Platform

  HEADLINE OP: given an outcome metric + entity, rank which other metrics best explain the outcome. Auto-selects candidates from the ontology if `candidates` is omitted (same topic + entity_type). Returns a ranking with confidence labels (strong/suggestive/weak/inconclusive) + reason strings + sharpen-suggestions pointing at related domains not yet included. Frequencies are auto-aligned to the coarser common grain — no inflated n-counts. Use this instead of `find_drivers` when you want a narrative-grade answer.

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• principles.search

  AI Design Blueprint Doctrine

  Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.

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• get_nursing_diagnosis

  CarePlanKit — Nursing Care Plans

  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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• principles.search

  AI Design Blueprint

  Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.

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• list_topics

  flevy

  The canonical list of management topics Flevy's catalog is organized under, each with its known aliases (e.g. "Digital Transformation" and "Digital Transformation Strategy" may be the same topic) and content counts. Use this to map a user's phrasing to the exact topic filter accepted by search_content, or to show what subject areas Flevy covers.

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• seo_keyword_research

  mcp-knowledge

  SEO keyword research from a seed keyword or topic. Uses Google Suggest (public, keyless) to discover related queries at 2 expansion levels, then clusters them by intent: informational / commercial / transactional / navigational — via heuristic pattern matching. Search volume is bucketed (very_high / high / medium / low / very_low) and clearly labelled as ESTIMATED — no fabricated precise numbers. Returns all keywords, intent clusters, quality scores (0-100), and top 10 opportunities. Supports country (gl) and language (hl) targeting. 100% keyless. Cache TTL 6h. ICP: SEO managers, content strategists, SaaS founders, agency teams.

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• seo_keyword_research

  gapup-mcp

  SEO keyword research from a seed keyword or topic. Uses Google Suggest (public, keyless) to discover related queries at 2 expansion levels, then clusters them by intent: informational / commercial / transactional / navigational — via heuristic pattern matching. Search volume is bucketed (very_high / high / medium / low / very_low) and clearly labelled as ESTIMATED — no fabricated precise numbers. Returns all keywords, intent clusters, quality scores (0-100), and top 10 opportunities. Supports country (gl) and language (hl) targeting. 100% keyless. Cache TTL 6h. ICP: SEO managers, content strategists, SaaS founders, agency teams.

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• get_timeline_by_id

  newtqnia

  Returns one published timeline. Administrators get the complete bilingual record with every event, source, and related link, plus access to draft content. Other accounts get a single locale (pass the caller's language in locale): each event's title, summary, media, sources, and related links, plus a canonical URL to the full timeline - never event bodies or the timeline introduction/conclusion.

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• research_bulk

  TrendFlow

  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_skill

  wondel-skills-mcp

  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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• search_situations

  clstr

  Search the news by topic to find matching situations and events. A situation is an ongoing storyline (story arc) that groups related events over time; an event, called a cluster, is one happening assembled from many outlets and deduplicated into a single item, so you get one event rather than 20 near-duplicate headlines. Results come back grouped under their situations, each with a one-line summary, a significance score (1 to 10, where 8 and above is exceptional), a source count (how many outlets are covering it), and a canonical clstr.news link. Use this to answer 'what is happening around X' for a topic, company, country, or event. Then open a result with get_situation_timeline for the full history, or get_cluster for one event's detail. Results are relevance ordered and bounded to the top matches: when there are more, the result ends with a cursor to pass back, and each page counts as one search against your cap. Cite the returned URLs. (Requires a free API key: https://clstr.news/developers)

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• search

  Vascue Public Knowledge Search

  Hybrid keyword + semantic search over the public pages of vascue.io: healthcare-operations guides, the AI front desk for clinics, provider-side insurance-claims automation, Cliniko and Nookal integration, security and compliance pages, case studies, pricing and blog posts. Use it to answer questions about what Vascue offers, how its products work and what it has published. One topic per call; cite the returned page URL for every excerpt you use. Returns a JSON text payload: result.chunks[] ordered by relevance, each with text (a Markdown excerpt), score (0-1, higher is better) and item.metadata.url (the canonical https://www.vascue.io/... page). Off-topic queries still return the nearest chunks, so treat scores below about 0.5 as weak evidence and say so when the site does not cover a topic. Read-only and idempotent; no authentication; 60 requests per minute per client. Public content only: never send patient information, claim documents, clinic credentials or booking requests. It cannot book appointments or look up clinic data.

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• search

  Vascue Public Knowledge Search

  Hybrid keyword + semantic search over the public pages of vascue.io: healthcare-operations guides, the AI front desk for clinics, provider-side insurance-claims automation, Cliniko and Nookal integration, security and compliance pages, case studies, pricing and blog posts. Use it to answer questions about what Vascue offers, how its products work and what it has published. One topic per call; cite the returned page URL for every excerpt you use. Returns a JSON text payload: result.chunks[] ordered by relevance, each with text (a Markdown excerpt), score (0-1, higher is better) and item.metadata.url (the canonical https://www.vascue.io/... page). Off-topic queries still return the nearest chunks, so treat scores below about 0.5 as weak evidence and say so when the site does not cover a topic. Read-only and idempotent; no authentication; 60 requests per minute per client. Public content only: never send patient information, claim documents, clinic credentials or booking requests. It cannot book appointments or look up clinic data.

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• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

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• address_related_addresses

  Nansen

  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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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• get_ticket

  Sweeppea MCP

  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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