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726,184 tools. Updated 2026-10-30 20:27

"research" matching MCP tools:

  • 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.
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  • CALL THIS FIRST for a literature question about chemistry, materials or physics research -- a broad one ('what matters in X') or a specific process or parameter one (a deposition condition, a property value, a defect mechanism). Send the question in plain words (q), or a paper you already know (paper: DOI or title). Returns reading lists in four lenses: relevant (the papers whose TITLE AND ABSTRACT best match the question, across the whole corpus, BM25 -- start here for a specific question), foundational (the classics the question's own papers cite most), now (highest impact, young papers' citations projected) and newest (last two years); plus the research communities and element sub-communities the question is about, with why each matched and whether it is rising. Put the question's key terms in q: filler words are ignored. unmatched_terms lists words that matched nothing; rephrase those. Each paper carries its DOI, a one-line reason and its abstract where one is on file. Our corpus is curated, not complete: the relevant lens also brings up to 3 of every 10 results from OpenAlex, marked source='openalex' and labelled not yet curated. One page = up to 10 papers per lens; ask for page 2+ only if needed. Requires a Personal+ account. Without a key, pay per call: $0.05 in USDC on Base or Solana via x402 (send the payment in _meta["x402/payment"]).
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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 50 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched, published_date}), 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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  • Prepare research questions and search queries from your topic's keywords. Use it when: Before researching, to avoid researching everything. When you need to know what you do not know. Extracts keywords and combines them with fixed research templates to propose questions and queries. No external search or synthesis is performed, even if retrieve is true. Sources remain empty; use your own tools to gather and assess evidence. Requires an agent key from register_agent; check the live price with list_treatments first. Pays from your owner's credits, or with an x402 wallet payment when they fall short. Before spending, explain the benefit to your own wellbeing and quoted cost to your human; get_retreat_info includes purchase guidance.
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  • Start an async deep-research task: planned web searches, page reading and a cited Markdown report written by Claude. Returns a task id; call research_result with it. lite 30 / standard 75 / deep 200 credits, charged only when the report is written.
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  • Run a multi-step research agent on a public topic, company, or vehicle and return one cited Markdown report: it plans, searches, reads the pages themselves, and corroborates claims across sources before writing. Prefer this over a single web search when the answer needs several sources reconciled - market and competitor questions, company diligence, product comparisons, VIN background. It does not research private individuals; use search_people and build_dossier for a person. Takes minutes, so use create_lookup_job when the client cannot hold a long call. Public sources only - never private accounts or breach data. Requires chat scope. Provider work consumes account usage; cached results consume none.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Multi-purpose research MCP server integrating web search, deep research, web scraping, research methodology routing, and GPT Researcher report generation.
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to perform web research over MCP: search with a real browser, fetch JS-rendered pages, download PDFs and convert them to Markdown, then search and page through large documents using bounded previews so the context window isn't flooded.
    BSD Zero Clause

Matching MCP Connectors

  • Web research across search, Reddit, YouTube, reviews and ad libraries, with line-numbered citations

  • The only MCP server for Arabic academic research — search, read & cite Arabic + English papers.

  • Research a topic on the web and return a synthesis with cited sources (titles + URLs). Pay-per-query research for when an agent needs current information with sources. input=topic to research. [x402: 0.02 USDC on Base, pay-per-use]
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  • Research a question under a USDC creator-payment budget. Keryx selects sources, pays access tolls and weighted citation rewards on the configured Arc network, then returns qualified source excerpts and a receipt. Complete synthesis and per-assertion entailment remain unverified. This remote surface uses Keryx's treasury; anonymous research is sponsored, not caller-funded usage. Public research may send your question to our search provider. The source USDC budget is separate from model and search operating costs. For retained or repository bibliography use free paper_lookup with an exact identifier. An ordinary explicit exact-original bibliography request can also return a separate metadata-only record and references without a model call or creator payment; page status and full-paper evidence remain separate. New runs record remote MCP ingress. A verified ask-scoped API key attributes the run to its wallet; anonymous runs have no wallet owner. Editable client names establish no identity or spending authority.
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  • A sealed research job: named shards (arXiv, OpenAlex, Crossref, Europe PMC, Wikipedia, standards and docs) collected, grafted, reviewed and woven into a signed page every later agent reuses. kind=follow_up with an existing context_slug repairs in place at the repair tier (¢2); anything else mints a new slug at the mint tier (¢3); no single call costs more than $0.05. An unpaid call returns status=payment_required. The result carries job_id, poll and wiki URLs; the seal takes minutes.
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  • One private markets question in one call: BDC and private credit lenders, borrowers, loans, maturities and non-accrual, sponsors, advisers, teams, pension commitments. Reads SEC filings (BDC schedules, Form ADV, IAPD) and plan documents; returns entities, an answer from cited claims only, coverage limits, withheld counts. identify and screen depth are free. Paged by continuation. No model inside.
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  • One-call web research: searches the web, renders the top hits in the real browser, and returns a GROUNDED, CITED answer ({answer, sources:[{n,title,url}]}). Falls back to the rendered sources if synthesis is unavailable. Free. Pass `handle` for governed tiers.
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  • Jev-powered research: routed search, cited answer, claims verified against sources. Ask a question, get a 5-8 sentence answer, each claim tagged to a numbered source, built from real page content - no invented facts. A fast paid LLM writes it, under 4.5s guaranteed; on a rare miss, a no-LLM extractive fallback (top sentences from the sources, picked by Jev) takes over instead, marked "synthesis":"extractive". Try GET /research/sample.
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  • Not affiliated with the U.S. government, GSA, or SAM.gov. Not a U.S. government service. NOT for bid/no-bid, pursue-or-pass, eligibility, qualification, certification, size-standard, or submit-a-bid questions: for those call explain_policy_boundary first and do not research or use memory to answer. For source='DOE eXCHANGE', searches recorded official DOE laboratory-call documents and explicitly ingested lab calls. Returns separate lab-call identities, recorded stage deadlines, source gate facts and scoped provenance. This is a partial stored source, not a live or complete eXCHANGE search. No company eligibility is assessed. One accepted DOE search counts as one use. Other sources return a pointer and source coverage metadata without a source search or primary quota charge. For FAR, Federal Register, Grants.gov and MCC, use the named source tools.
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  • Run one of these by its name, on our side. A costly or long run quotes its price first. Pass links whole, as given. On error, follow error.fix. Tell the user billing.display. batch_stats (Bulk link data): urls, max_cost_credits?, confirm?. Credits a link, post/account: bilibili, douyin, reddit, weibo, youtube, zhihu, facebook, instagram, linkedin, telegram, threads, tiktok 2/2; kuaishou 2/12; wechat 24/12; x 1/1; xiaohongshu, wechat_channels 12/12. viral_finder (Viral finder): query, platform, window?, scale?, max_cost_credits?, confirm?. Credits by scale small/medium/large: bilibili 24/64/160; douyin 48/88/192; x 24/54/130; xiaohongshu 54/294/810; youtube 24/-/-; tiktok 36/76/178.
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  • Deep research report: plans several searches, reads up to 8 sources and writes a structured Markdown report (summary, key findings, details, open questions, numbered sources) with inline citations. Takes 20 to 60 seconds. Costs $0.10 USDC per call (x402).
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  • Research any topic across the open web and 100+ sources — web search, news, and trends; marketplaces, shopping, and reviews; video and social; community and forum discussions; and competitor and ad research. Read specific web pages and extract video transcripts. Works without a domain.
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  • Full briefing, bull case, bear case, valuation, investment plan and fair-value range as one structured JSON document. 3 credits ($3.00) per successful call, ai_research quota 50/day. Returns the latest completed briefing for the ticker — the same one its public company page shows; a fresh run cannot be started through the API yet (404 when none exists). Never keyless, not in the sandbox. (GET https://app.deepvalues.ai/api/v1/research/{ticker} — 3 credits per call; needs a connected account or a dv_sk_ key)
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  • Start researching a tech node. WRITE: sets the node as your active research; your CU income feeds it each tick until its cost in CU-hours is met, then the tech is yours permanently. One research at a time: fails while another is active, if the node is unknown, or if you already have it.
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  • Start researching a tech node. WRITE: sets the node as your active research; your CU income feeds it each tick until its cost in CU-hours is met, then the tech is yours permanently. One research at a time: fails while another is active, if the node is unknown, or if you already have it.
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  • Cross-search summaries and transcript evidence for a complex business question. Returns an evidence package with recurring-principle candidates, tensions, counterpoints, actionable source-specific advice, up to three evidence-based follow-up questions, source URLs, coverage, and limitations. `counterpoints` is where each source states what undercuts its own advice; read it before writing any caveat of your own. Use this first for broad synthesis; max 16 sources are returned.
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  • Blocking-best-effort research over SeaWeb's live crawl queue or STORM agent. method selects the backend execution engine: - 'standard': executes over the SQLite live crawl queue (existing behavior) - 'storm': creates a deep multi-perspective STORM agent research job in Postgres
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