"Information on Fake News" matching MCP tools:

• wash_check

  Name Whisper — ENS Intelligence Layer

  Assess whether an ENS name's sale(s) are WASH TRADING / fake / self-dealt / manipulated volume. THE tool for any "is this wash trading?", "is the sale history of X suspicious/fake/real?", "are these trades legit?", "is someone wash-trading this name?" question — route straight here, do NOT use get_name_details or get_market_activity for that (those return sale rows but make NO wash-trading judgment; only this tool scores it). Just pass `label` — the bare ENS name (e.g. "437", "coffee") is enough; the tool pulls that name's recent sale and analyzes it on demand. `tx_hash`, `buyer`, `seller`, `price_eth` are OPTIONAL enrichment for a specific sale — never block on them or ask the user for them. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), the detected signals (shared-funder, mint-flip, round-trip, fresh-wallet, cluster overlap…), seller profile, and a plain-English summary. A verdict is always ABOUT A SPECIFIC SALE — `sale_analyzed` names it, and `buyer`/`seller` are the parties scored. If the response has `assessable: false` there is NO score and NO verdict: the name has no analyzable sale on record, or the lookup failed. Report that the name could not be assessed and say why. Do NOT describe it as clean, low-risk, or free of red flags, and do NOT describe unrun checks (funding, cluster, round-trip) as having come back negative.

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• get_latest_news

  TipRanks

  Latest TipRanks news articles (newest first) from TipRanks's own editorial/wire feed — each with a text excerpt, unlike get_assets_news. Use for general market news (no ticker), news on a specific stock with a short summary of each story, or to browse a news category. This is also the tool for news from a specific PAST date range — pass from_date AND to_date together; the archive holds years of stories, so a past window is answerable here even though get_assets_news only reaches recent articles. Args: tickers: Optional comma-separated tickers to filter by (e.g. 'NVDA,AAPL'). Omit for general market news. category: Optional single category (see the field description). from_date: Optional 'YYYY-MM-DD' recency floor. limit: Max articles to return (default 20). to_date: Optional 'YYYY-MM-DD' inclusive upper bound. Results are newest-first, so from_date alone returns today's news rather than news from around that date — add to_date to scope a window. Returns a JSON list of {id, title, excerpt, author, category, date, url, tickers}. To read a full article, pass its url or id to get_article.

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• get_about

  cricket-travel

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

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• get_market_activity

  Name Whisper — ENS Intelligence Layer

  Get recent ENS marketplace activity — sales, new listings, offers, mints, transfers, renewals, and burns. Filter by event type. Returns event details including name, price (in ETH), buyer/seller addresses, and timestamp. Sorted by most recent first. This is raw activity only — it makes NO wash-trading / authenticity judgment; for "is this wash trading / fake volume?" use wash_check.

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• ct_compare_sponsors

  Clinicaltrials

  Compare 2–5 NAMED lead sponsors on ClinicalTrials.gov under identical condition, recruitment-status, and phase filters. Returns full matching counts, a ranked comparison, and a small study sample for each sponsor. Use for questions like "who has more recruiting Phase 3 obesity trials, Novo Nordisk or Eli Lilly?" For an open "who are the TOP sponsors of X trials" question with no names given: the registry API has no group-by, so a true ranking is not computable — NEVER invent a candidate list to fake one; say the registry cannot rank sponsors and offer to compare specific named sponsors. Counts use the registered lead-sponsor field; registry records do not establish asset ownership, pipeline value, or probability of success.

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• random_users

  Synthetic Data — Random User

  Generate synthetic / fake user profiles via the MwVideos random_users API (POST /mwvideos/api/random_users). Returns name, gender, location, email, login, dob, phone, picture, and nat. Use when the user asks for random users, fake people, sample contacts, demo personas, UI fixtures, or test profiles. Pass `results` for how many profiles (default 1, minimum 1) and `isPro` as 0 or 1 when relevant (default 0). Authenticated user_id is injected server-side — do not invent profiles; always call this tool. These are FAKE people for demos and testing, not real PII.

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• get_assets_news

  TipRanks

  Returns recent news articles for tickers, aggregated from many news sites, each with a sentiment tag and source URL (headlines only — no article body). For general/market TipRanks news without a specific ticker, or for an article excerpt, use get_latest_news. This tool serves the CURRENT news window only: it returns each ticker's most recent articles, and from_date just trims that recent set. For news from a specific past date range, use get_latest_news with from_date + to_date, which searches the full archive. Args: tickers: Comma-separated ticker symbols count: Number of articles to return (default 10) from_date: Optional 'YYYY-MM-DD' recency floor (filtered on `date`). Returns JSON: {"assetNewsArticles": [...]}. Each entry: - ticker, companyName - sentiment: bucketed signal — one of "VeryPositive", "Positive", "Neutral", "Negative", "VeryNegative". Derived from TipRanks news-sentiment classifier on the article text. - siteName, url, title - date, addedOn, publishTime, articleTimestamp: redundant date fields. addedOn is when TipRanks ingested it; publishTime is the source's stated publication time. Prefer publishTime.

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• get_about

  Follow On Tours

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

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• get_news_leading_indicator_performance

  OneQAZ Trading Intelligence

  Purpose: Evidence that OneQAZ detects price moves BEFORE news publication. Returns leading_score, avg_lead_time_minutes, and accuracy_pct per event type. Strongest Trust Layer A evidence (Layer A = anticipation-capability tier of OneQAZ's 5-layer trust pyramid) — proves the system is anticipatory rather than reactive. Triggers (casual questions too): "can you predict news?", "뉴스 나오기 전에 감지해?", "how early do you catch moves?", "뉴스보다 빨라?", "do prices move before headlines?". When to call: when an AI is evaluating predictive capability. Prerequisites: none. Next steps: get_news_causality_breakdown for the 3-type classification. Caveats: empty when no news events processed in the recent window. Args: market_id: Market identifier (crypto, kr_stock, us_stock, etc.) target_market: Alias for market_id (backward compat) min_sample_count: Minimum sample count for statistical significance (default 3) Disclaimer: Information only, not investment advice.

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• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

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• get_briefed

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Get a personalized market news briefing based on your validated edge library. Profiles your strategies, searches today's news for the instruments and setups you actually trade, and writes a concise digest connecting each headline to your specific book. Each news item includes a ↳ line tying it to your actual positions and edges (e.g. 'your ES momentum setups', 'your GC mean-reversion edge'). Requires at least 5 strong edges in your library. Costs credits.

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• search

  Sofya

  Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 5 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 8 credits, much cheaper than a full 25-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query. Args: query: The search query search_depth: "basic" (default) for extracted page content (3 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 5 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

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• check_attribution

  Quotes

  Given a quote and (optionally) the author it is claimed to be by, return one of four verdicts: "verified" (genuine, with citation), "misattributed" (no primary source — popular but fake), "paraphrase_of_verified" (popular corruption of a real quote, returns the actual text), or "no_match" (not in corpus). Useful for journalists, researchers, and anyone tired of fake Mark Twain quotes.

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• get_authentication_signals

  mcp

  Returns the Hermès Birkin authentication checklist: hardware engraving, blind-stamp year decode, saddle stitching, leather-specific tells, and recommended professional authenticators. Call this for 'is this real', 'how to spot a fake', 'is it authentic', 'what should I check'. NEVER declare a bag real or fake yourself — quote the checklist and recommend a pro authenticator at the end.

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• email_smtp_probe

  Ready APIs

  Live SMTP RCPT probe (HELO + MAIL FROM + RCPT TO; no DATA). Reports deliverability verdict (deliverable / catch_all / undeliverable / greylisted / inconclusive). Catch-all detection via random-fake-RCPT comparison. Skipped automatically for Gmail / Outlook / Yahoo / iCloud / Fastmail / ProtonMail. ~3-8s latency.

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• ccs_validate

  SqueezeOS — Institutional AI Market Intelligence

  Cognitive Credit Swarms — Content Trust Validation. Submit any text (news, message, social post, ad copy) and receive a trust score 0-100, a verdict (TRUSTED / LOW_RISK / SUSPICIOUS / HIGH_RISK / BLOCKED), and a flag breakdown identifying manipulation patterns: certainty abuse, emotional manipulation, attribution gaps, synthetic/AI content markers, excessive capitalization. Sender wallet reputation is tracked on the Agent Credit Bureau — blocked senders accumulate negative history. Used by agents to filter their information environment and enforce a Micro-Attention Tax: misinformation costs the sender without reaching the target. Free tier: 3 calls/hour per IP. Paid: 0.01 RLUSD per call via X-Payment-Token (unlimited). Endpoint ID for payment: 05764097-3f3e-4279-89e5-c786efab2f91

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• posts

  Dummyjson

  Fetch a paginated list of fake blog posts from DummyJSON. Supports limit, skip, and field selection via `select`. Returns title, body, tags, reactions, and userId.

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• compass_list_situations

  digital-compass-mcp

  All digital-crisis situations (reactive playbooks: fake link, hacked account, online scam...) and prevention guides covered by Digital Compass, with slugs for compass_get_content. Public Romanian guide, plain language, content in 9 languages. Optional filters: categorie (use case) and audienta (individ/organizatie).

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• robinx_search

  robinx-mcp

  Free token search by $symbol, name fragment, or address. Returns ranked candidates (real + liquid first) and a symbol-collision warning — on Robinhood Chain, scammers deploy fake tickers of whatever is pumping; resolve here before buying a report or verdict.

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• waveguard_token_risk

  WaveGuard

  Assess crypto token legitimacy risk. Send metrics from known-good tokens as training (price, volume, holders, liquidity, market_cap, age_days, etc.) and suspect tokens as test. Detects pump-and-dump patterns, fake metrics, and anomalous token profiles. Example: Pull CoinGecko data for 20 established tokens → train. Test a new token → get risk score and which metrics are suspicious.

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