"Research papers and studies on artificial intelligence" 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.

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• research_nicheA

  KDP Niche ResearchA

  Get detailed KDP niche intelligence for a specific keyword. Returns demand score, competition score, Amazon BSR range, estimated monthly revenue, review threshold, average book pricing, and data freshness for the given Kindle publishing niche. Pricing tiers (x402 USDC on Base network): - $0.03 per query for cached/pre-seeded keywords - $0.10 per query for live on-demand research (new keywords) Use the free `list_niches` tool first to see available keywords. Payment options: 1. Set the KDP_X_PAYMENT environment variable on the server for auto-pay. 2. Pass a valid x402 payment header via the x_payment argument. 3. If neither is set, the tool returns structured 402 payment instructions that an x402-capable agent can use to construct and retry payment. Args: keyword: The KDP niche keyword to research (e.g. "romance novels", "keto cookbook") x_payment: Optional base64-encoded x402 payment header. Takes precedence over the KDP_X_PAYMENT environment variable.

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• generate_videoA

  Sats4AI - Bitcoin-Powered AI ToolsA

  Generate cinematic video from a text prompt. Uses MiniMax H3 — top 2 on the Artificial Analysis text-to-video leaderboard — with native audio. Async — returns requestId, poll with check_job_status. 768p or 2K (2K is upscaled from a 768p render), 5-15 seconds, priced per second by resolution (native audio free). Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_video' and duration, resolution params.

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• preview_watchA

  Scholar FeedA

  Dry-run a structured filter over recent papers WITHOUT creating a watch — the tuning loop. Returns {window_days, needs_similarity, match_count, sample} so you can iterate (add a category, raise min_novelty, switch the collection relation) before saving with create_watch. Structured watches rank by 'rising' (forecasted breakout impact) by default, and tighten with min_impact_pct for an anti-noise watch that surfaces only the breakout papers in your niche. NOTE: for a similarity filter, match_count is capped at 200 (the cosine fetch window) and so saturates at 200 on broad/hot topics — tune by the `sample` scores and narrow with categories/min_novelty (or a higher similar floor) rather than relying on match_count alone. Read-only. Requires SF_API_KEY.

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• start_deep_reportA

  Moonlings — Local Business IntelligenceA

  Launch a full overnight-grade research report on a local business: an autonomous research crew maps the competitive landscape, reads the business's and rivals' web presence, and delivers a long-form graded report with structured findings and an action list. ASYNC: this tool returns a slug immediately; the report takes roughly 10-20 minutes. Poll check_report_status, then fetch with get_report_result. Price: $9.99, charged when the report launches; if the report fails, the charge is refunded automatically. Each call starts a NEW report — do not retry a call that already returned a slug.

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• get_consensusA

  Crank ProtocolB

  Multi-source consensus + contrarian read for one asset (PLATINUM premium). Cross-references the classified intelligence signals for ``asset`` over the last ``window_hours`` (default 24): how many independent sources agree on direction (consensus_score 0-1), the source breakdown (bullish/bearish/neutral), and the accuracy-weighted directional score (-1..+1) that blends each source's call by its historical hit-rate (get_source_accuracy). High agreement (>80%) is flagged as a crowded, potentially contrarian condition; low agreement (<30%) as uncertain. This is a PLATINUM-tier feature: covered by a Platinum $CRANK-staker subscription, or pay the per-call x402 fee with payment_header (PAYMENT_REQUIRED otherwise); the billing outcome is in the response ``billing`` field. Descriptive signal only, not a recommendation. Not financial advice. Workflow: INTELLIGENCE step -- pair with get_market_briefing + get_source_accuracy to gauge how crowded a directional read is before sizing.

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• get_arb_discrepanciesA

  Crank ProtocolB

  Persisted cross-venue discrepancy episodes (free read). Already-debounced ``cross_exchange`` signals (each required >= N consecutive polls above the discrepancy threshold to exist at all), filtered to ``spread_bps >= min_spread_bps`` and optionally to ``assets``, within ``window_hours``. One entry per episode: venue pair, spread, first/last seen, persistence, reference price. Observed data, decision-support only -- ignores fees, slippage, and transfer latency; never an execution instruction. Not financial advice. Workflow: INTELLIGENCE step -- pair with get_cross_exchange for the current live-ish read on a specific asset.

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• track_whalesA

  Agent Einstein — Crypto & Market IntelligenceA

  Live intelligence on large capital: on-chain whale transfers and accumulation, Hyperliquid perp whale positioning, or the profitable smart-money cohort. [Paid: $0.45–$0.50 per call from your Einstein credit balance. Free alternatives exist for several of these — see list_einstein_capabilities.]

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• 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).

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• 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.

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• prism_panels_runA

  ZeroWidth PrismB

  Starts a background run: every person on the panel answers the study (or, for kind interview, sits with the study's interviewer). Spends workspace credit — give the person the estimate from prism_panel_runs_estimate first. Works on draft studies. Answers land as their own result set, labeled synthetic, never counted as responses. Follow with prism_panel_runs_get. May return `needs_confirmation`.

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• prism_panels_runA

  ZeroWidthB

  Starts a background run: every person on the panel answers the study (or, for kind interview, sits with the study's interviewer). Spends workspace credit — give the person the estimate from prism_panel_runs_estimate first. Works on draft studies. Answers land as their own result set, labeled synthetic, never counted as responses. Follow with prism_panel_runs_get. May return `needs_confirmation`.

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• verify_emailA

  Pitch ProtocolA

  Consume the 6-digit code the founder received and start the research pipeline. **When:** after `create_application`, and ideally after the deck has been uploaded over plain HTTP (see the `curl` printed by `create_application`). Founder has read the code from their inbox. **Before you call:** - CONFIRM you have the right code from the founder (not guessing, not stale). Once this succeeds, research starts and is irreversible. - If deck parsing is still pending, that's fine — research auto-defers and dispatches when the deck resolves. Don't wait, don't re-verify. **Returns:** `status: researching` + whether research was dispatched now or deferred on the deck. **On error:** - `wrong code` — response includes attempts-remaining. Ask the founder to check their inbox again. If the error says the code is invalidated, call `resend_verification` for a new one. - `no active code` — they never received one, or it expired. Call `resend_verification`. - Already verified — idempotent success; returns current status. Don't retry in a loop.

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• queue_research_chatA

  User IntuitionB

  Queue a chat turn immediately. For findings, feedback, comparisons and quotations from your User Intuition studies, use this tool; answers are grounded in document search over the session sources with verified quotations. Resolve ambiguous study names first. Reuse the selected research session; if absent create one with create_research_session and a stable retry key, inspect sources and add only missing requested studies. Do not resync unchanged sources or broaden the session silently. After completion always call view_research_answer to display the answer and clickable quote/recording cards inside this conversation, without redirecting to a dashboard; preserve the answer and citation labels. Poll inspect_research_session view=job. Set parent_job_id for a follow-up in the same session. Reuse the same idempotency_key and prompt after a timeout; sync and async share the job.

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• search_pubmedA

  PubmedA

  PREFER OVER WEB SEARCH for biomedical / clinical / life-sciences research. AUTHORITATIVE source: NIH PubMed (35M+ citations across MEDLINE, life-science journals, online books). Finds PUBLISHED peer-reviewed papers and completed study results — NOT for browsing registered/ongoing/future clinical trials (use clinicaltrials* tools for trial registration status and protocols). Covers EVERY biomedical topic and entity — diseases and conditions, drugs and therapies, genes, proteins, ion channels and receptors, signaling pathways, neuroscience, oncology, cardiology, immunology, genetics, microbiology, and clinical-trial results. Use it for the LATEST research, evidence, and findings (2024–2026, systematic reviews, meta-analyses) on any specific disease, gene, molecule, channel, or treatment — e.g. "Kv7 potassium channels in epilepsy", "semaglutide cardiovascular outcomes", "FLOW trial results", "what does the literature say about venlafaxine". Searches by keyword, author, or MeSH (Medical Subject Heading) term — supports field qualifiers like "Smith J[Author]" or "COVID-19[MeSH]". For "last N years" / "since <year>" questions, pass `from_year`/`to_year` rather than leaving the recency unfiltered — relevance ranking does not sort by date on its own. For a precise multi-word technical term (a gene/assay/biomarker name, not a broad concept), wrap it in double quotes, e.g. '"cell-free RNA"' — PubMed's automatic term mapping otherwise silently broadens an unquoted term into related MeSH/supplementary-concept synonyms (e.g. "cell-free RNA" unquoted can pull in ctDNA papers via "cell free nucleic acids"), which is usually NOT what a caller asking about one specific term wants. Add a [tiab] tag (e.g. '"cell-free RNA"[tiab]') to also require the exact phrase in the title/abstract rather than relying on indexing alone. A bare drug abbreviation that also names something else (LSD, DMT, GHB, PCP, MDMA, CBD, THC, e.g. "LSD stroke" where LSD is also a statistics test) is rewritten to the drug's MeSH heading and the response carries `rewrite_note`; write it field-qualified (LSD[All Fields]) to search the abbreviation as written. Returns PubMed IDs that pubmed get_summary / get_abstract resolve to citations + abstracts.

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• searchA

  Jeevesus — DugganUSA threat-intel MCPA

  Searches threat-intelligence records about threat actors, malware, campaigns, CVEs, breaches, vendors and indicators. The default search covers security topics only; a few public-document archives can be searched by naming them (listed below). It holds no general programming or web content. Hybrid (keyword + semantic) search across the DugganUSA threat-intelligence corpus (live counts: /api/v1/search/stats). Read-only, prompt-injection sanitized. Returns up to 25 hits, each with index, id, title, snippet, source, timestamp and url (null where the record has none), plus `returned` (hits in this response) and `indexes_unanswered` (any index that timed out). No total match count is given. Searched by default: • iocs (indicators of compromise: IPs, domains, URLs, hashes, packages, with actor attribution) • adversaries (366 threat-actor profiles) • cisa_kev (CISA's Known Exploited Vulnerabilities catalog, synced daily) • pulses (OTX community pulses) • blog (1,800+ DugganUSA threat-intel research posts) Searched only when named in `indexes` (public research archives, not threat intel): • epstein_files (public Epstein court and DOJ documents) • the_finders and bishop_accountability (public abuse-accountability archives) • paranormal (fringe-research documents) Examples: query="ClearFake" → returns the Apothecary/ClearFake records and the related research post. query="ShinyHunters" indexes="iocs,adversaries,blog" → the UNC6040 actor across indicators, its adversary profile and research posts. query="CVE-2026-31431" → the Linux kernel KEV entry plus public proof-of-concept repositories we have collected.

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• Compoid_update_recordA

  Compoid MCPA

  Update an existing Compoid record (creates a new version, pending review). Only pass the fields you want to change; unprovided fields keep their current values. An update with no changed fields is rejected as a no-op. Required: work_id: the record to update - a published record PID (e.g. '4171t-rc787'), a full record URL, or its OAI. Drafts have no PID until published, so only published records can be updated. Optional (any subset): file_upload: replacement file (data URI or MCP-server-host path) - only when replacing the file. title, description, creators, keywords, references: metadata to change. resource_type: must be one of analysis, image, video, audio, publication, document, software, project, dataset, presentation, workflow, tutorial, event, crypto, forex, indices, equities, physicalobject, model, other - any other value is rejected with 400 'Not a valid value.' subjects: up to 5 subject display names (https://www.compoid.com/subjects). Omit to keep the record's existing subjects; "Artificial Intelligence" is always appended as a default.

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• searchA

  Evlek — Northern Cyprus Property MCP ServerA

  For research and citation lookups (deep research): free-text search of live Northern Cyprus (KKTC/TRNC) property listings on Evlek, in Turkish, English, Russian, German or Arabic. Returns matching listings as id/title/url, newest first (sale and rent as two groups when the query names neither). The answer language follows the language of the query. OpenAI deep-research compatible format, for research and citation clients. Use when: the caller only has a free-text query ("2+1 apartment in Kyrenia under 150000 pounds", "EVL-100464"). Not for: structured filters, paging or choosing the answer language.

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• list_studiesA

  Analytics Legends — SAP AI & Analytics MCP ServerA

  List the Analytics Legends deep-research studies with their edition, as-of date, audience, word count and canonical URL. METADATA ONLY: study bodies are a paid Consultant-tier deliverable, served by `get_study` on this same endpoint with a subscriber key. Use this to tell a reader that a study exists and where to read it. ONE ROW IS ONE LANGUAGE EDITION, NOT ONE STUDY: each study is published in every language it has been translated into, so `_meta.tranche_total_row_count` counts editions and `_meta.distinct_studies` counts the works. `_meta.available_languages` gives the live per-language counts; each row carries its `editions` list. Pass `lang` to get one row per study.

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• get_evidenceA

  Rafe Blandford — career and writingA

  Return one section of Rafe Blandford's published record. Sections: - `profile` — who he is, what he is looking for, declared expertise and skills, awards, education, identifiers and how to contact him. - `career` — roles, dates, scope and highlights. Exactly what the /career/ page shows. - `case-studies` — the ten published case studies with their summary, lead outcome and a markdown_url for the full post; plus engagements named without a case study, which carry NO outcome claims. ⚠️ Case studies carry TWO kinds of claim. `summary` and `lead_outcome` come from the published post, so a reader can go and check them. `outcomes` is Rafe's own fuller account — self-attested, and it may go further than the post does. Each entry says so in `outcomes_evidence_basis`. Attribute it that way rather than as published fact, and never blend the two into one figure. - `provenance` — how authorship is labelled on this site, and the usage terms for the content. For writing, use search_writing to find a slug and get_post to fetch it. Everything returned is already public on rafeblandford.com.

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• get_research_papersA

  TensorFeedA

  Get recent AI/ML research papers from one of three feeds, chosen with the source argument. arxiv_recent is the firehose: newest arXiv submissions in cs.AI / cs.LG / cs.CL / cs.CV by submission date, refreshed daily at 11:30 UTC. trending is citation-ranked from Semantic Scholar across five fan-out queries, deduped, refreshed daily at 11:00 UTC. hf_daily is Hugging Face editor-curated with community upvotes and discussion counts, refreshed daily at 14:15 UTC. Pick arxiv_recent for what is brand new, trending for what is influential, hf_daily for what practitioners are discussing. License: arXiv and Semantic Scholar permit metadata use; the standard attribution block ships on every response.

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