"research" matching MCP tools:

• research

  Agentcy - Your AI Marketing Agent

  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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• research

  Sofya

  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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• research

  tela

  Answer a question — or gather everything relevant on a topic — from the wiki by MEANING. One call assembles answer-ready grounding: the full bodies of the pages that matter (not isolated fragments), pulled from pages AND attached files (PDFs, docs), plus any flagged disagreements among the sources and a low_confidence signal. Returns `context` (a numbered [n] excerpt block to ground your answer), `sources` (the cited hits aligned to [n], each with page_id/chunk_id for drill-in and a download_url for file sources), `disagreements` (conflicts to surface, [n]-keyed), and `low_confidence`. YOU write the answer from `context` and cite sources by their [n]. To read one section deeper use `read_chunk` (chunk_id from a source) or `get_page` (full page). For exact-name/term lookup use `search`. Requires a configured embedder (503 otherwise).

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• research

  WingmanProtocol Agent Gateway

  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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• research

  Omnicall — Agent Tools Gateway

  Multi-platform meta-search — web, GitHub, Hacker News, Stack Overflow, arXiv, academic papers, Wikipedia, news in ONE ca Cost: $0.005–$0.05 USDC on Base per call.

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• research

  Prism — Data Enrichment for AI Agents

  Multi-platform meta-search — web, GitHub, Hacker News, Stack Overflow, arXiv, academic papers, Wikipedia, news in ONE ca Cost: $0.005–$0.05 USDC on Base per call.

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• weather-research-brief

  The Stall

  Weather-contextualized research intelligence — pulls historical weather for any location (ERA5 reanalysis via Open-Meteo) and multi-source research on any topic (Hacker News, OpenAlex academic papers, Reddit, arXiv, DuckDuckGo), then synthesizes them into a unified brief showing how weather conditions amplify or inform the research findings. Ideal for agricultural commodity analysis, climate/energy positioning, supply chain risk, insurance/actuarial, and environmental due diligence.

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• research-paper-search

  The Stall

  Academic paper search across 250M+ works via OpenAlex (free, no key). Returns top papers with title, authors, year, DOI, citation count, open-access status, and primary research topic. Covers all disciplines: AI/ML, medicine, physics, economics, law, biology, and more. Supports relevance, citation-count, and recency sorting; open-access filtering; and year-range constraints. Use for literature review, prior-art search, citation building, or finding the seminal papers in any field.

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• research-automation-brief

  The Stall

  Automated research intelligence: combines deep topic synthesis (Hacker News, OpenAlex academic papers, Reddit, arXiv, DuckDuckGo) with scheduling guidance in a single call. Returns a structured research report — executive summary, key findings, sentiment, emerging trends, and recommendations — plus a validated cron schedule, recommended cadence, freshness window, and automation notes for recurring unattended runs. Ideal for developers building scheduled intelligence pipelines, agent builders setting up recurring research feeds, and teams that need to monitor a topic on autopilot. Works across any domain: markets, technology, science, geopolitics, and more.

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• company-research-bundle

  The Stall

  Entity-parametric company research in one call: live stock quote, quarterly income statements, and Wikipedia background. Optionally adds GitHub repo analysis and website intelligence when those inputs are provided. Parallel-safe for enriching lists of companies in distributed agentic pipelines. Replaces 3–5 individual cap calls; entity-parametric (one ticker per call).

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• research-synthesis

  The Stall

  AI-synthesized intelligence report on any topic — aggregates Hacker News, OpenAlex academic papers, Reddit, arXiv preprints, and DuckDuckGo in parallel, then distills into a structured report: executive summary, key findings, market sentiment, emerging trends, and recommendations. Works across domains: financial markets, macroeconomics, technology, life sciences, geopolitics, and more. Pass ?query=your+topic for targeted research. Omit query for a default AI agents & autonomous systems report.

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• research-report

  arch-tools-mcp

  Generate a structured AI research report on any topic. Searches multiple sources and synthesizes findings into executive summary, key findings, and conclusion with citations.

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• youtube-keyword-research

  The Stall

  YouTube keyword research using Google's autocomplete API. For a seed topic, returns suggested search phrases plus intent clusters: questions people ask, tutorial/learning queries, comparison queries, and year-tagged trending terms. No API key. Upstream of youtube-niche-intel (competition scoring) and youtube-intel (video search). Use when mapping a YouTube content strategy, finding keyword gaps, or building a channel topic plan.

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• model-research-brief

  The Stall

  AI/ML domain intelligence in one call: discover top HuggingFace models for a task or domain plus a synthesized research brief from HN, OpenAlex, Reddit, and arXiv. Returns model rankings, landscape summary, research trends, and a deployment recommendation.

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• buy_credits

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Buy credits for the edge library and AI research. Default $5 minimum. Free — no credits consumed to call this. TWO PAYMENT METHODS: card (default): Returns a Stripe Checkout link for your user to click and pay. After payment, call check_balance to confirm credits were added. crypto: USDC on Base. Fully autonomous — no human needed. Three steps: 1. buy_credits(payment_method='crypto') → returns deposit address + payment_intent_id 2. Send USDC to the deposit address (use your wallet tool) 3. buy_credits(payment_intent_id='pi_...') → confirms payment, credits added instantly If you have wallet access, this is the fastest path — fully machine-to-machine.

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• web_research

  DialogBrain

  Answer a research question from live web sources in one call — returns a synthesized answer with numbered [N] citation markers and a citations array of {url, title, index}. Supports recency and domain filters. Use for questions needing current, sourced information (news about a company, market state, comparisons). For raw search result links use web.search; mode='deep' runs minutes-long exhaustive research — only when explicitly requested.

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• research_niche

  KDP Niche Research

  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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• lion_deep_research

  LION x402 - Keyless Attested Enrichment & Signals for AI Agents

  ONE-CALL attested company/crypto deep research. Pass ?q=<company, domain, or topic> (and optional ?domain=, ?num=, ?receipt=1). LION runs web search -> scrapes the top source -> firmographics enrich (Wikidata + SEC) -> domain trust, and merges them into one Ed25519-attested JSON — replacing StableEnrich's 3-4 call research loop (~$0.08) with a single $0.012 call (~85% cheaper). For company research, vendor due diligence, business intelligence, SEC financials, and crypto/token research. Keyless, no account, no PII. For people/email/LinkedIn/maps use stableenrich.dev — LION proves companies. Volume: ?volume=100 -> $0.010, ?volume=1000 -> $0.008. [x402 paid tool: GET /api/x402/deep-research-json?src=mcp returns the 402 challenge with the canonical payTo; price 0.012 USDC on Base eip155:8453.]

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• search_google_scholar

  Academic Research MCP Server

  Query Google Scholar for academic papers, citations, and research articles across all disciplines. Returns paper title, authors, publication venue, citation count, abstract preview, and full-text link if available. Use for comprehensive literature searches, citation tracking, or finding highly-cited works.

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• legislation_get_section

  UK Legal Research

  USE THIS TOOL WHEN you have a known Act / SI and want the parsed text of a specific section, with extent and in-force metadata. Returns full section text, territorial extent, in-force status, and prospective flag. Content capped per max_chars (default 10,000, ~2,500 tokens) — raise for unusually long definition sections; check content_truncated in the response. ALWAYS check `extent` — a section may apply to England & Wales but not Scotland or Northern Ireland. Reciting a section without checking extent is a recurring legal-research error. Alternative: call read_resource(uri="legislation://{type}/{year}/{number}/ section/{section}") for raw CLML XML; use this tool when you want the parsed structured response instead.

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