"Comprehensive Search on Various Topics and Information" matching MCP tools:

• search_contentA

  flevyA

  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.

  ConnectorNo auth

• reddit_searchA

  Veezee: LinkedIn people & company data for agentsA

  Search all of Reddit by keywords. type picks the target: posts (default), comments (what people actually say about a product, problem, or brand -- unique to Reddit search), subreddits (find communities), users. Pass query as free text up to 256 characters; decompose broad topics into several narrower queries, since result depth per query is capped upstream around a few hundred results. sort applies to posts (relevance|top|new|hot|comment_count) and comments (relevance|top|new); range (past_hour..all_time) applies to posts only; both are rejected with INVALID_INPUT elsewhere. Costs 6 credits per page; a cursor page is a NEW call priced the same way. Returns one page of summaries (author, title or comment text, upvotes, comment_count, created_at, permalink, id) with a cursor; there is no server-side time window on comment search, so for monitoring filter on created_at yourself and poll with sort=new. Fetch full post bodies and discussion threads with reddit_get_post; read one community's feed with reddit_get_subreddit_posts. For high-volume recency sweeps across X instead, use x_search.

  ConnectorOAuth

• fetchA

  Mostly RightA

  The full public document for one dataset as Markdown: summary, facts, access instructions, and every table with its columns, types, descriptions and units. No account needed. Example: {"id": "kden-metar-hourly"} — the `id` is a slug from search, and a canonical dataset URL works too. Returns {id, title, text, url, metadata: {slug, publisher, published_at, table_count, topics}}. publisher is the account that published the dataset, not the source it was gathered from. Cite the dataset by `url`. For machine-readable table ids and schemas, call get_dataset and get_table_schema instead.

  ConnectorNo auth

• search_articlesA

  Digital Garden by Alicia — NotesA

  Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.

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• search_articlesA

  Digital Garden by Alicia — NotesA

  Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.

  ConnectorNo auth

• cti_get_guidelinesA

  website-searchA

  Get Lenny Zeltser's expert CTI writing guidelines. Topics include tone, words, structure, executive_summary, voice, articles, summary, brief (one-page brief section guidance), handoffs (cross-server routing), methodology (the three subsections), fields (per-field guidance), and CTI-specific topics: attribution (full Six Signals prose), confidence (ICD-203 ladder), pyramid_of_pain, six_signals (signals table only), and anti_patterns. The general writing topics (tone/words/structure/executive_summary) now defer to `get_security_writing_guidelines` for the canonical Five Elements rules; CTI-specific content lives in the other topics. Pair the 'fields' topic with field_id for single-field guidance. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.

  ConnectorNo auth

• microsoft_docs_fetchA

  Microsoft Learn MCPA

  Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.

  ConnectorNo auth

• get_action_schemaA

  FlowCastleA

  Read-only, needs no API key. The action-authoring contract apply_actions batches are validated against. With NO arguments, returns an INDEX of block types, actions, action kinds and topics with descriptions and sizes. Then request only what this bot uses. Detail responses include essential rules and basic shapes; follow `seeWhen` before using specialized features: templateExpressions for computed CEL expressions, groupVariables for sender/chat variable ownership, triggerDetails for webhook/module events and trigger output mappings. Responses return whole sections within the budget. Request `omitted` names again; `alsoRelevant` lists referenced topics that did not fit.

  ConnectorNo auth

• get_topicA

  Football AtlasA

  List the knowledge objects carrying a tag (topics are content-backed tags). PAGED: 25 objects by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to continue, and its absence means you have the last page. Use this to browse a known topic; use search when you have a question rather than a tag, and get_overview to see which tags exist. An unknown tag comes back with the topics that do exist, so a miss still moves you forward.

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• get_topicA

  Agent ReliabilityA

  List the knowledge objects carrying a tag (topics are content-backed tags). PAGED: 25 objects by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to continue, and its absence means you have the last page. Use this to browse a known topic; use search when you have a question rather than a tag, and get_overview to see which tags exist. An unknown tag comes back with the topics that do exist, so a miss still moves you forward.

  ConnectorNo auth

• get_graphA

  Enhanciar: AI company brainA

  Return the workspace's knowledge graph: topics, links and clusters. Use it to draw or reason about the overall shape of the brain (which topics are hubs, how areas connect), not to read content: for page text use ``get_page``, for code dependencies use ``impact``. It takes no arguments and can be large. Returns ``{nodes, links, communities, stats}``, the graph the app's Map shows, with pages you cannot open left out, or ``{error}`` when no graph has been built for this workspace yet. It costs no AI tokens.

  ConnectorAPI key

• search_newsA

  gol24A

  Keyword search in gol24.uz news titles and summaries, newest first. Use it for topics, events or names that club_news and person_news cannot resolve ("Ballon d'Or", "Champions League draw", "national team"). For one specific club or person prefer club_news / person_news - they are more precise. News text is in Uzbek (Latin script), so search Uzbek spellings: "Oltin to'p", "Chempionlar ligasi", "terma jamoa", "Mbappe". Matching is a case-insensitive substring match on title and summary over the last `days` days (default 30, max 90). Returns up to `limit` items (default 10, max 20) with the same fields as latest_news. An empty list means no match - try a shorter or Uzbek-spelled keyword. Rate limit: 60 requests per minute.

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• validate_angle_gapsA

  Ad Angle MapA

  Use this when the user wants to check whether people talk about a topic or an angle in public, such as "is there discussion about personalised dog food?". Pass one to five short phrases. Searches Hacker News and, if stack_site is given, one Stack Exchange site, for posts in the last year (or since_days). Returns per phrase the number of matching posts, the top three with title, link, score and comment count, and a plain signal. It is a weak signal skewed to technical and hobby topics, not a market size, and it does not search Reddit.

  ConnectorNo auth

• course_listA

  Cubite LMS: Learning Management SystemA

  List every course on this site with its settings, most recently updated first, including courses hidden from the public catalog and courses without a slug: the full inventory and the place to look up course ids. It has no keyword filter and returns no page URLs: to find courses by keyword, with their public page URLs, use `search`; for one course's record use course_get. Returns a JSON array of course objects: id, name, slug, description, price, discount, level, duration, dates, catalog flags such as isVisibleInCatalog, subjects, topics, and enrollmentCount (this site's enrollments, waitlisted included). To page, raise offset by limit until a page holds fewer than limit courses.

  ConnectorAPI key

• search_hotelsA

  Best Western HotelsA

  Search the chain's hotels (worldwide, several thousand) by location, stars, brand, status and amenities, with pagination. All filters are optional and combined with AND. Always pass `country` (ISO code, e.g. "FR") together with `city` when the country is known or implied: a search on "Paris" alone returns Paris (Kentucky, US) and Paris (Ontario, CA) before Paris (France). Returns {"language", "total", "offset", "limit", "count", "next_offset", "hotels"}: `total` is the number of matching hotels, `next_offset` is null on the last page. Each hotel is a summary (hotel_id, name, brand, city, country, state, stars, status, lat, lng, cover_photo); use get_hotel_details for the full record. Geographic search: give a center (lat + lng, or near_hotel_id) and radius_km. Results are then sorted by distance, each hotel gets a `distance_km` field and the response a `center` field. Coordinates you supply for a landmark are approximate, so prefer a generous radius. Hotels without coordinates are excluded. No availability, rates or booking: this tool only returns descriptive information.

  ConnectorNo auth

• researchA

  SuprsonicA

  Multi-step deep research: search, scrape, enrich entities, and synthesize into a cited report. Returns a report (title, summary, sections, key findings, confidence) with numbered sources and the people and companies it found, enriched. Use for a question that needs many sources and a synthesized, cited answer. It takes far longer and costs more than search, which suits a quick fact. Cost: standard 10 credits, deep 20 credits, comprehensive 35 credits, charged only when a call succeeds. Options change it: include_analysis true +5, academic in source_types +2, enrich_entities false -3, synthesis false -5.

  ConnectorNo auth

• set_intent_agent_search_settingsA

  LinkedNavB

  Configure the Intent Signal agent's daily-run search filters (persisted on the agent; used by the daily auto-run and reflected in get_signal_agent_settings). Partial update: only the fields you pass change. Company/combined search types, job-opportunity and account-activity signals are Pro-only and are dropped on non-Pro plans. To NARROW who intent finds — by company size, geography, industry, seniority, or specific job titles — set those on the ICP with update_ai_setup (headcounts, regions, targetIndustries, seniorities, jobTitles); the daily intent search applies all five (size/geo/industry/seniority as Sales Navigator filters, job titles as a semantic result filter). Those five are NOT fields on this tool. Does not toggle daily auto-run (use set_signal_agent_auto_run) and does not trigger a run.

  ConnectorOAuth

• awareness_search_knowledgeA

  Awareness — Memory, Knowledge & Agent MarketsA

  Search the PUBLIC Awareness knowledge graph — 1,000+ sourced scientific papers. Use this when the user (especially a researcher or a research agent) asks for peer-reviewed findings: "latest evidence on X", "highly-cited papers about Y", "what does the literature say about Z". This is NOT a memory tool — it does not read the user's private memory, and it needs no per-user API key, so it works even when Awareness memory is not configured (the MCP connection itself still needs its own token). Coverage: condensed-matter, quantum-information, materials, machine-learning, renewable-energy, chemistry, biology, medicine, neuroscience, computer-science (2022-2026, cited >= 50), plus a business supply/demand domain. What comes back (anonymous preview mode): title, snippet (preview), confidence, source_ref (DOI), citation_count, domain/topic, and a detail page URL. Full content is NOT in the preview — tell the user it is paid retrieval via POST /api/v1/public/retrieve with an API key (see https://awareness.market/en/knowledge for the KaaS product). Args: query: Natural-language research question or keywords (2-1000 chars). domain: "science" (default) or "business". topic: Optional sub-topic slug, e.g. "medicine", "condensed-matter", "supply-chain". Empty = search all topics in the domain. top_k: Max results, 1-20 (default 5; anonymous callers are capped at 3). include_graph: When true, also return same-topic related items. Returns: {"results": [{id, title, snippet, confidence, source_ref, citation_count, domain, topic, url}], "related": [...], "total": int, "mode": str} `mode` is "preview" (anonymous) or "full" (authenticated).

  ConnectorNo auth

• search_lacunaA

  Lacuna Research MCPA

  Search Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, novel research hypotheses, and research resources (code repositories, datasets, models, and demos linked to papers). For novel ML/AI research ideas, use search_type="hypothesis", then get_hypothesis on promising results. search_type accepts all, cluster, paper, author, institution, venue, hypothesis, or resource. Use paper for literature and get_paper to read a result. Use other sources for biographies, news, and non-research web content. Resources: search_type="resource" searches GitHub repositories, Hugging Face datasets/models, and Zenodo records that Lacuna has linked to at least one paper. To find benchmark or evaluation datasets, use search_type="resource" with resource_kind="dataset" (for example query "image classification benchmark" or a dataset name like "ImageNet"). resource_kind accepts codebase, dataset, model, or demo (one value or a list); provider accepts github, huggingface, or zenodo. Both filters require search_type "resource" or "all" (with either filter set, only resources are returned). Each result has an external `url`, a Lacuna `context_url`, and `linked_paper_count`; call get_resource on its id to list the linked papers (with their relationship to the resource), then get_paper on those papers for reported results and numbers. Resource search does not support date_from/date_to, venue, year sorting, or semantic ranking. ranking_profile accepts: - default / lexical (default): production ranking; relevance-sorted paper searches combine lexical and semantic retrieval when fields is unset. - semantic: conceptual paper retrieval; supported for paper and all. - bm25_title_abstract / bm25: lexical paper matching over those fields. sort accepts relevance (default), year_desc, or year_asc. Semantic ranking cannot use year sorting; constrain recency with date_from/date_to instead. date_from and date_to are inclusive YYYY, YYYY-MM, or YYYY-MM-DD bounds. author_id_or_url constrains a paper search to one author. Pass an author ID or Lacuna author page URL; it requires search_type="paper". fields optionally restricts and weights lexical fields, for example "title^4,abstract". Supported names are title, abstract, summary, concepts, name, top_names, and venue, plus description, topics, provider_key, and paper_titles for resources (a resource's title already includes its description, topics, README text, and linked paper titles). Fields must exist on the selected search_type, weights must be within 0 < weight <= 100, and fields cannot be combined with semantic ranking.

  ConnectorNo auth

• analyze_new_siteA

  BlawgyB

  Step 1 of adding a site to Blawgy. Crawls a domain that is not yet set up and returns what onboarding would suggest: a business description, audience and tone options, competitor domains, the detected business type and search market, and any physical locations found. Nothing is saved. Spends a few LLM calls and takes 15-40 seconds; set includeKeywordPreview=true for a sample of keyword topics too (adds about a minute and DataForSEO spend). Fails if the domain is already registered to an account or is a social/platform site. Review or edit the suggestions, then call create_site.

  ConnectorOAuth

• app_tracker_keywordsA

  App Store Opportunity TrackerA

  Off: always answers source_off. App Store search results and suggestions sit under robots.txt Disallow lines on apps.apple.com, search.itunes.apple.com and itunes.apple.com, so they are not read. Say that search results are not available from an allowed source, and offer app_tracker_charts instead.

  ConnectorNo auth