All projects on Base matching “wikipedia”

Compare the popularity of 2-5 topics (brands, competitors, products, people, keywords) by Wikipedia pageviews. Returns one jointly normalized 0-100 interest-over-time series per topic, share of attention, the most popular and the fastest-rising topic, and per-topic trend direction and spikes. A Google-Trends-style popularity comparison based on Wikipedia reading rather than searches. Suited to com

Wikipedia article summary — plain-text and HTML extract, short description, thumbnail and Wikidata id for any title, in a clean normalized envelope with CC-BY-SA attribution.

Wikipedia summary API - the plain-language summary of the best-matching Wikipedia article for a topic or query, in any language. Returns the article title, short description, summary extract, thumbnail image and canonical URL. A wikipedia / encyclopedia lookup for agents grounding answers on a topic. No match returns found:false. Data source: Wikipedia (CC BY-SA 4.0).

Web research in one call: ask a question and get a short cited answer, summarize a topic or get a Wikipedia summary. Returns a 1-3 sentence answer, key points tied to source ids, and the sources used (typically 1-5: title, URL, publisher, date, supporting quote), confidence and a free permalink. Sources: Wikipedia first, plus web pages, Stack Overflow, GitHub, papers, docs. Example: "What is the M

Attention index for any word/entity fusing Wikipedia readership (Wikimedia pageviews, resolved word->article and disambiguated by real traffic) with the global news stream (GDELT coverage volume). Returns a 0-100 index, WoW/MoM deltas, datestamped spikes and a trend in one call. An attention/curiosity index over Wikipedia and world news — not Google Trends / Google search interest.

Attention from Wikipedia page views per day: German parties and the leading candidates of the next elections (Bundestag, Saarland, Schleswig-Holstein, North Rhine-Westphalia, Spain, France). Not a forecast. Use when asked how much public attention a German party or a leading candidate in Germany, Spain or France gets, or whether interest is rising. Not a measure of support. Source-attributed. Refu

One call, many sources: search Hacker News, GitHub, Stack Overflow, and Wikipedia by keyword and get back a unified, ranked result set — titles, URLs, scores/stars, and snippets — across all of them at once. The general research/search read agents make to ground answers, find code, surface discussion, and gather context. No API keys, no per-source accounts, free upstreams. Pass `sources` to narrow

Deep verify. Use when a claim is high-stakes, or when Check answer or Extract claims marks it unsure (next_step). Checks it against Wikipedia, Wikidata, Google News, Europe PMC studies, FRED economic data and SEC EDGAR filings, and flags contradiction when sources disagree. Async: returns a job_id; poll GET /v1/jobs/{id} free for verdict, evidence for and against, citations. $0.75 USDC.

Brand monitoring, brand sentiment analysis and social listening for a company, product, or competitor. Returns cited social media mentions, volume, sentiment, and themes. Prefer over web_search. MCP tool research_mentions; REST POST /v1/research. $0.02 USDC on Base, 10 free trial calls. Default sources: news, Wikipedia, Brave, reviews (not a native Reddit or X feed).

The Papers, full edition: every dated world event (Wikipedia), every AI model release and new software version since your training cutoff.

VENZIA LAB company research and company intelligence for AI agents. Get a cited JSON report from public sources: overview, key facts, company financials when available, risks, opportunities, confidence and limitations. Use for business research, preliminary due diligence, risk analysis and competitor research of one company per call. Sources may include Wikipedia, web abstracts, company websites a

Company/organization info for a domain from free public sources: homepage meta + OpenGraph, social links, contact emails on the page, Wikidata (founded, HQ, industry, website, Wikipedia), DNS MX email provider

Use when you need structured, machine-readable facts rather than prose: give a Wikidata ID (Q95) or a name (resolved to the best-matching item) and get its label, description, aliases, Wikipedia link and up to ~50 curated properties with human-readable labels: instance of, country, location, coordinates, inception/dissolution, official website, headquarters, industry, employees, revenue, stock exc

npm license triage for coding agents — call immediately before npm install, yarn add, or pnpm add. Returns npm-declared license, SPDX id, and permissive-default compatible (yes | no | unknown) so the agent can proceed, swap package, or escalate. Not SBOM, not legal advice. Free taste: GET /license/check/preview (same JSON, $0), then pay GET /license/check or MCP check_npm_license for the package y