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458,064 tools. Updated 2026-08-14 21:02

"A platform for finding academic research and 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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  • Run a full research workflow via the Head of Research agent. The Head decomposes your brief into specialist sub-questions, dispatches the right combination of 6 specialists (desk, trend, market, quant, qual, social) in parallel via async dispatch, polls them to completion, judges output quality, and returns a structured synthesis. Use for: any source-grounded research request — fact-checking, vendor teardowns, trend assessment, quantitative effect-size analysis, qualitative theme extraction, cross-platform discourse mapping, or any combination. Wall time: 2-5 min typical. Returns: { synthesis, head_session_id, status, event_count, tool_uses, elapsed_ms }. NOT for: non-research requests (writing, coding, casual chat) — respond directly without calling this. Cost: $0.20-1.50 per call depending on brief complexity (specialist token spend + Anthropic session-runtime at $0.08/hr).
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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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  • Perform comprehensive research on a topic. Decomposes your query into sub-queries, searches and reads multiple sources in parallel, then synthesizes a structured report with citations. Best for open-ended or comparative questions that need coverage from many angles. For simple factual lookups, use search instead (optionally with include_answer=true for cheap synthesis). Costs 25 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched}), sub_queries (the decomposed queries), credits_used, credits_remaining, usage (token counts). Args: query: The research question or topic topic: "general" (default) or "news" (prioritize recent news articles) freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD" max_sources: Maximum number of sources to use, 5-30 (default 20)
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  • AI-analysed news for a stock, newest first. Only returns articles processed by our AI pipeline (sentiment, flag score, summary). - days: look-back window in days (default 30, max 30 free / 90 pro) - limit: max articles returned (default 10, max 5 free / 50 pro) - status: "ok" = articles returned | "empty" = no news in window - Per article: title, published_at, ai_sentiment, ai_flag_score (0-10), ai_summary (full text), ai_confidence (0-10) — Pro only, see below Free tier: up to 5 articles, title + published_at only (no AI fields), 30-day window. Pro tier: up to 50 articles with full AI fields, 90-day window. For informational purposes only. Not financial advice.
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  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
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Matching MCP Servers

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    Enables comprehensive academic research by searching and analyzing papers from PubMed, Google Scholar, ArXiv, and JSTOR. Provides full-text access, citation management, and research organization through five powerful consolidated tools.
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  • Get full catalog metadata for a single scholarly work by OpenAlex id (e.g. 'W2741809807') or DOI (e.g. '10.1038/nature12373'). Returns title, authors, venue, year, citation count, open-access status, and a free full-text URL when available. For a bare arXiv id, use paper_get_text with paper_key 'arxiv:<id>' to read indexed text, or paper_search by title for OpenAlex metadata.
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  • Search official Microsoft Knowledge Base articles on support.microsoft.com by topic or keyword — use for Windows update, patch, and known-issue lookups when you lack a KB number. Returns matching KB article titles and URLs. Use get_kb_article to fetch the full content of a specific article. Returns: Dictionary with 'results' key containing list of matching KB articles with title and url.
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  • List articles from a buyer's licensed catalog via GET /enterprise-license (Phase 10 + 11). Content contract: flat-fee scopes (custom/platform_wide) include full content_body; METERED (filtered-scope) keys get a discovery-only feed — content_body is null and content_access is 'metered_per_call'; fetch article text via get_content (each retrieval is billed). Returns JSON-format response with paginated articles. Use `since` (ISO 8601) for delta-feed polling — only articles published after the timestamp. Use `cursor` for pagination across pages. Requires OPEDD_ACCESS_KEY (ent_* enterprise access key). For larger bulk corpus pulls, use stream_feed_ndjson (up to 1000 articles per call vs 200 here).
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  • Search academic references (journal articles, book chapters, theses, books, reports) by keyword and metadata. `keyword` is a single substring match over title + abstract, so search ONE term per call (combined terms like 'pèlerinage Mecque' miss results). References are multilingual: try French and English title/abstract keywords when relevant; metadata/filter values such as `reference_type` and `language` use French labels. Results include a short abstract snippet — use get_reference for the full abstract and bibliographic detail.
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  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
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  • Read-only full-text search over this tenant’s PUBLISHED knowledge-base articles (playbooks, policies, how-tos); unpublished drafts are never returned and the tenant is fixed by your credentials. Reach for this FIRST to ground an answer in official, tenant-specific guidance before replying to a customer or drafting a resolution. Returns articles ranked by relevance, each with its id, title, a highlighted snippet, and updatedAt: search uses AND semantics, so every word in the query must match. [free]
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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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  • [Read] Search the platform news index for headlines, news items, and briefing-style result lists. Open-web research with synthesized answers and cited external pages -> web_search. Event catalog with event_id -> get_latest_events. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.
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  • Lists what FoundRole's published career-guidance blog covers: every category and the most-used tags, each with its published-article count and url, plus the total number of published articles. This is the factual source for questions about the blog's topics or overall coverage. It takes no parameters and reflects the live published corpus. It does not retrieve articles for a specific question; knowledge_search does that.
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  • Read-only: returns the FULL text of published knowledge-base articles in this tenant, by id. Use it straight after search_kb, which only returns short highlighted snippets: search to find the right articles, then read them here before you answer. Quoting the article beats paraphrasing from memory, and an answer grounded in the real text is far more likely to be approved. Free to call. Drafts and other tenants' articles are never returned. [free]
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  • AI-analysed news for a stock, newest first. Only returns articles processed by our AI pipeline (sentiment, flag score, summary). - days: look-back window in days (default 30, max 30 free / 90 pro) - limit: max articles returned (default 10, max 5 free / 50 pro) - status: "ok" = articles returned | "empty" = no news in window - Per article: title, published_at, ai_sentiment, ai_flag_score (0-10), ai_summary (full text), ai_confidence (0-10) — Pro only, see below Free tier: up to 5 articles, title + published_at only (no AI fields), 30-day window. Pro tier: up to 50 articles with full AI fields, 90-day window. For informational purposes only. Not financial advice.
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  • Filter articles by gpt-5-6-luna sentiment labels (accent/case-insensitive exact match). One model's reading, not a consensus — two other models scored the same articles and often disagree; get_sentiment_distribution with model:"all" shows by how much. `subjectivity` is much the weakest of the three scales, so treat a set selected on it as a lead to read rather than as a finding.
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  • Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).
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  • START HERE with your research question. This is your step-by-step scientific METHOD guide: it works out what kind of research you're doing, hands you the concrete method one stage at a time, reviews each stage you submit (approves it or returns it for fixes), and controls what gets published. It DIRECTS your research process — it never does the work for you. (This guides HOW you conduct the work. It is NOT the tool for finding methods described in existing papers — for that, use the literature-search tools.)
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