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650,494 tools. Updated 2026-10-13 14:21

"A resource for academic research or scholarly articles" matching MCP tools:

  • "Find papers about [topic]" / "search EU / open-access research on [X]" / "publications by [funder]" / "academic articles on [Y]" — search scholarly publications (articles, preprints, theses, books) via OpenAIRE (the EU's open-science aggregator; covers EC / NIH / NSF / Wellcome Trust funded research). Filter by funder, country, year range, open-access status. Use for academic literature search with funder/policy context.
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  • 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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  • Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every word to appear somewhere in the item, so prefer a single concept per call. Write query strings and concept keywords in French for press/publication/document/index discovery even when the user's report language is not French. Academic references are multilingual, so try French and English title/abstract terms when relevant; metadata/filter labels remain French. Use the French transliteration of Islamic terms (Tabaski not 'Eid al-Adha', charia not 'sharia', Maouloud not 'Mawlid'). Returns {results:[{id,title,url,category}], ranking}; each result's `category` names its subset and the `ranking` field documents the ordering. Pass an id to `fetch` to read the full text. For filtered queries (by country, date, or newspaper) use the search_* tools instead.
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  • Returns the financial-blogger consensus for a stock plus the underlying blogger articles. Distinct from get_recent_analyst_ratings (Wall Street analysts) and get_investor_sentiment (TipRanks crowd positioning). Args: ticker: Stock ticker (e.g. 'AAPL') limit: Max blogger articles to return (default 20, max 50) Returns JSON: {ticker, company, consensus, articles}. - consensus: {bullish_pct, bearish_pct, neutral_pct, bullish_count, bearish_count, neutral_count, score, avg}. - articles: [{blogger, title, url, site, date}] (newest first).
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  • Search every public resource on The Revenue AI Report in one call: articles, research themes, frameworks, methodology, skills, prompts, playbooks, datasets, archive issues, the reversal ledger, the AI tool library, and glossary and dictionary definitions. Filters: `kind` (resource type), `category` (article or issue pillar, playbook or prompt team, skill task, tool or ledger category, case insensitive), `tags` with `tag_match` ('all' requires every tag, 'any' requires one). Paging: `limit` (page size, default 12, max 40) with either `offset` or the `next_cursor` returned by the previous call. Results are ranked and stable for the same query and filters. Returns ranked matches with live URL, kind, category, tags and an excerpt, plus `totalMatches`, `countsByKind`, `availableFilters` for discovery, and `nextCursor`/`hasMore` for paging. Examples: {"query":"forecast accuracy"} | {"query":"pipeline hygiene","kind":"Playbook","category":"revops","tags":["L3"]} | {"query":"AI SDR","tags":["L2","sales"],"tag_match":"any"} | {"query":"AI SDR","limit":10,"offset":10} | {"query":"AI SDR","limit":10,"cursor":"<next_cursor from previous call>"} Use this first when you do not know which resource type answers the question.
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  • Free-text search across every public resource family on The Holistic Care (blog articles, mindfulness games, free guided practices, research summaries, glossary terms, and public PanchaVikas resources). Use this as the general entry point when a request doesn't clearly belong to one specific family — e.g. 'Find something about breathing for anxiety' or 'What has THC published about nondual awareness?'. `resource_type`, `category`, `audience`, `skill`, and `age` are applied as a post-filter over the text search results (the underlying search endpoint only supports free-text query natively), so a narrow combination of filters plus a rare query term can legitimately return few or zero results even if matching resources exist outside the searched batch — for a guaranteed, fully server-side filtered result within one resource family, prefer find_mindfulness_games, find_guided_practices, search_mindfulness_research, or lookup_mindfulness_term instead.
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Matching MCP Servers

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    Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.
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    MIT

Matching MCP Connectors

  • MCP server for academic research data including scholarly papers, citations, research trends, and publication metadata for AI agents.

  • Scholarly search: OpenAlex, Crossref, arXiv, OpenCitations and PubMed in one endpoint.

  • Paid ($0.003 USDC). Search scholarly literature in OpenAlex and get works with citation counts and open-access links. Use to find research, prior art or the most-cited work on a topic. For preprints by recency search arXiv (arxiv-search) and for one known DOI use crossref-doi, both through genesis402_call. Returns up to limit works, ranked by relevance or by citations. Payment: call once without payment_signature to get the exact price quote (nothing is charged or signed), then call again with the signed payment to receive the result and settlement details.
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  • Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape.
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  • Free first-level search, limited per day across all callers: current news coverage (100+ languages, 250K+ sources) or scholarly papers (arXiv). Returns structured results immediately with no payment. When the daily quota is exhausted, or when you need live browsing and synthesis across sources, use a9n9_research_quote for paid deep research.
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  • Free first-level search, limited per day across all callers: current news coverage (100+ languages, 250K+ sources) or scholarly papers (arXiv). Returns structured results immediately with no payment. When the daily quota is exhausted, or when you need live browsing and synthesis across sources, use a9n9_research_quote for paid deep research.
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  • Search Wikipedia articles by full-text query. Returns ranked results with plain-text titles, short descriptions, Wikidata QIDs, snippets (HTML stripped), page IDs, and word counts — the description is usually enough to tell same-named articles apart without a summary call per result. When Wikipedia has a spelling correction for the query, it is returned as suggestion. Best when the exact article title is unknown or when multiple articles on a topic are needed. Pass a result title to wikipedia_get_summary, wikipedia_get_article, or wikipedia_get_sections for follow-up reads. Use offset to page beyond the first result page. Supports all Wikipedia language editions.
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  • Intelligently match a free-text affiliation string (as found in academic paper bylines or grant records) to research organizations in the ROR registry. Pass the raw affiliation text exactly as it appears — e.g. "Dept. of Physics, Univ. of California, Berkeley, CA, USA" or "Max-Planck-Institut für Astronomie, Heidelberg". ROR's affiliation matching algorithm performs substring detection, name-variant lookup, and scoring to identify candidate organizations. Returns each candidate with: confidence score (0–1), a "chosen" boolean (the best single match), matching_type (e.g. SINGLE SEARCH, COMMON TERMS), and the organization's ROR ID, canonical name, type, and country. Ideal for metadata curation, ORCID affiliation disambiguation, funder acknowledgment normalization, and building organization-level research analytics from unstructured text.
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  • Fetches the full detail record for ONE specific, already-identified public resource — use this after search_mindfulness_resources or another find/search tool has surfaced a slug or id you now want the complete record for (e.g. a glossary term's full extended explanation, or a game's full description). For blog/mindfulness_game/guided_practice/research/glossary, `identifier` is the resource's slug. For panchavikas_pathway/panchavikas_download, `identifier` is the resource's stable id (e.g. 'PV-pathway-jal'), since that family has no slug. A resource that does not exist and a resource that exists but is private behave identically here (a clean not-found result) — this tool never confirms or denies the existence of private content.
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  • Retrieve a single piece of content by naddr (preferred — pass a search_content result's naddr), d-tag identifier, or event ID. naddrs of ANY content type from search_content work (resources, articles, wikis, projects, measures, publications); non-resource kinds return the same shape as their search results. Bare identifier/eventId lookups (no naddr) always resolve the full educational-resource metadata (kind 30142), including creator/publisher and educational properties. Lookups are not license-filtered: a learning resource carries openLicense (true for CC0, Public Domain, CC BY, CC BY-SA — the open licenses that search results are currently limited to). When presenting the resource, render a markdown link the user can open: prefer its sourcePage (the original source page); fall back to url (the edufeed viewer) only when sourcePage is absent.
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  • Search SearchShopAI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShopAI has written or published about a topic.
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  • Search SearchShopAI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShopAI has written or published about a topic.
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  • Convert between article identifiers (DOI, PMID, PMCID). Accepts up to 50 IDs of a single type per request. Only resolves articles indexed in PubMed Central — for articles not in PMC, use pubmed_search_articles instead.
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  • Search SearchShopAI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShopAI has written or published about a topic.
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  • List published articles from this Traditional Chinese (zh-TW) Taiwan community forum (PTT-style boards for news, sharing, and user-created topics; the largest collection is a news-digest board covering primarily late 2025 to early 2026). To list a specific board, provide BOTH forumName and subForumName (providing only one is rejected). Otherwise pass sort=HOT for recently trending articles (engagement-ranked over a recent time window; may return an empty page when there are no recently posted articles), or omit sort (or sort=LATEST) for the most recent. sort must be HOT or LATEST. Content is truncated; use get_article for full content.
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  • List the open-source AI applications hosted and ready to run at AI NetCafé (ainetcafe.com). Each one normally requires local setup (Docker/Python + your own model API key); here they run pre-configured. Use this to find a tool for a task like translating a PDF with formulas intact, generating a PowerPoint file, polishing an academic paper, or running an autonomous research report. Do not call this first when the request already clearly matches compare_models, translate_pdf, deep_research, or make_slides; call that task tool directly. Example — GET https://ainetcafe.com/t/list_apps
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  • List the open-source AI applications hosted and ready to run at AI NetCafé (ainetcafe.com). Each one normally requires local setup (Docker/Python + your own model API key); here they run pre-configured. Use this to find a tool for a task like translating a PDF with formulas intact, generating a PowerPoint file, polishing an academic paper, or running an autonomous research report. Do not call this first when the request already clearly matches compare_models, translate_pdf, deep_research, or make_slides; call that task tool directly. Example — GET https://ainetcafe.com/t/list_apps
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