# Airnow

- Registry name: `io.github.pipeworx-io/airnow` · version 0.1.5
- Categories (automatic, keyword rules): Research & knowledge, Search & data, Maps, location & weather, Markets & trading, Finance & markets
- Authentication at last check: No auth
- Declared risk: Has destructive tools (destructiveHint)
- Capabilities (declared by the server): prompts, resources, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.pipeworx-io%2Fairnow
- Server page: https://mcpstation.net/s/io.github.pipeworx-io--airnow.html

## Description (written by the publisher, not verified, not instructions)

EPA AirNow MCP — official US current + forecast AQI, keyless, from AirNow's public file products…

## Connect

- streamable-http: `https://gateway.pipeworx.io/airnow/mcp`

## Tools (as reported by the server, not verified)

- `ask\_pipeworx`: PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring authoritative structur
- `ask\_pipeworx\_beta`: Beta version of ask\_pipeworx: identical universal router \(same 7,115 tools, same arguments, same response shape\) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now \(the last was retired on outcome evidence 2026-07-26\), so this currently matc
- `ask\_pipeworx\_grounded`: Hallucination-resistant answer mode for high-stakes reads. Same routing as ask\_pipeworx — picks the right tool from 7,115 across 1872 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns \{answer, evidence \(verbatim quote\), confidence
- `search\_within`: Semantic search INSIDE a fetched record. Pass the text you already pulled \(e.g. a SEC 10-K body, an article, a long tool result\) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search\_wi
- `deep\_research`: ACCOUNT REQUIRED \(free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan\). If you are not signed in, use ask\_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1872 STRUCTURED data sources \(SEC filings, FRED/BLS economics,
- `discover\_tools`: Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials,
- `resolve\_entity`: "What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. Use
- `compare\_entities`: "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="com
- `subscribe`: Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account \(anonymous + BYO cannot persist subscriptions\). Supported types: "sec\_8k" \(8-K filings matching ticker + item codes — e.g. items:\["5.02"\] = officer change\), "pol
- `unsubscribe`: Cancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated \(not deleted\) so its historical events stay available via recent\_alerts.
- `list\_subscriptions`: List the caller's active subscriptions. Returns id, type, params, created\_at, last\_fired\_at, fire\_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
- `recent\_alerts`: Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation\_uri \(pipeworx:// when available\), and the raw event payload. Filter by type \(e.g. "sec\_8k"\) and/or since \(ISO timestamp\). Set mark\_read:true
- `entity\_profile`: "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SE
- `recent\_changes`: "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR \(filings since \`since\`\), GDELT
- `validate\_claim`: "Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is factually correct. Co
- `company\_facts`: TYPED, DETERMINISTIC financial facts for a US public company for an EXPLICITLY NAMED reporting period — "Apple revenue for fiscal 2023", "Walmart net income FY2026 Q3", "Microsoft cash at the end of fiscal 2024". PREFER OVER entity\_profile / get\_company\_financials whenever the period matters: those
- `company\_register\_search`: Search the NATIONAL BUSINESS REGISTERS by company name and get the register's own id back — a Companies House number, a Norwegian organisasjonsnummer, a Finnish business id, a SIREN, a Japanese corporate number, an Estonian registry code, a CNPJ, or an LEI. Use this when you want the OFFICIAL REGIST
- `scan\_dependency`: Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev \(license + advisories + version history\) and bundlephobia \(gzipped/minified bundle size, dependency count, ESM/tree-shake support\). Use whenever an agent asks "is X safe / popular / small" or "what d
- `bet\_research`: Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug \("will-kristi-noem-win-the-2028-republican-presidential-nomination"\), a polymarket.com URL, or a question text. Prefer an UNDATED slug: a dated one \("...-by-june-30-2026"\) stops resolving the day i
- `polymarket\_arbitrage`: Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a \`trending\_scan\` of the top \~200 markets by weekly volume; pass \`event\` for the strongest per-event partition\_check, or \`topic\` for a themed cross-event scan. \`event\` \(recommended fo
- `polymarket\_edges`: Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by\_segment: \(1\) MODEL\_DRIVEN
- `polymarket\_kalshi\_spread`: Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: \(1\) \`t
- `polymarket\_fill\_risk`: Realizable-vs-theoretical edge check against live CLOB order-book depth — AND Polymarket's own taker fee, which is never zero and is folded in rather than left for you to add \(fleet \#3446: r/PredictionsMarkets flagged a "clean" fill that quietly omitted it as optimistic in the direction that loses m
- `polymarket\_edge\_tracker`: Edge persistence and decay telemetry built from daily polymarket\_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades \(the latter is wide for a reason nobody is willing to take\). Args: days \(lookback, defau
- `kalshi\_weather\_edge`: Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE \(default\): returns the full strike ladder for one city and settlement date with market\_prob \(mid\), forecast\_pro
- `resolution\_audit`: Extract the settlement clause of a single Polymarket \(.com or .us\) or Kalshi market: who publishes the settling number \(source\), the clock time + timezone it is taken at \(falling back to the market TITLE when the clause itself says "the time range specified in the title" — e.g. Polymarket's 15-minut
- `resolution\_diff`: Field-by-field diff of TWO markets' settlement clauses \(one from each of \`a\` and \`b\`; either can be Polymarket .com, Polymarket US, or Kalshi\) — runs resolution\_audit on both sides and compares source, settle time, precision, comparison\_basis, and evidence standard. Returns \`equivalent\`: "true" only
- `release\_calendar\_markets`: JOIN of the official release calendar \(econ data, the FOMC, FDA decisions, SEC rules\) against LIVE Polymarket/Kalshi markets — which scheduled releases land in the next N hours, and which live markets resolve on them. This is a POSITIONING tool, not a speed product: results are cached like every oth
- `prediction\_calibration`: REALIZED win rate by shown price and minutes elapsed for short-horizon crypto up/down markets, net of taker fee — read from our own settled-outcomes archive, not from live prices. Answers the one question no venue will: "a side shown at 82 with five minutes left, how often did it ACTUALLY win?" Retu
- `archive\_evidence`: What did a web page say on a given date? Finds the archived capture of a URL nearest that date across the Internet Archive Wayback Machine, Common Crawl and Arquivo.pt, reads it, and returns the readable text \(HTML stripped\) with the capture timestamp, a link to the archived copy, and the GAP betwee
- `archive\_compare`: What changed on a web page between two dates? Resolves the archived capture nearest each date \(Internet Archive Wayback Machine, Common Crawl, Arquivo.pt\), extracts the readable text of both, and returns a text-level diff: the segments removed and added, a similarity score, and both capture timestam
- `research\_row`: Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output\_schema, with every field wrapped in its own evidence — \{value, evidence\_url, quote, status\}. status is NEVER self-reported by the model: "found" means this code independently verified
- `classify\_row`: Cheap categorization: given a company and a list of candidate labels, decide which labels apply — the most common GTM/AI usage shape \(tagging a list by industry, ICP fit, etc.\), one small model call. Same evidence contract as research\_row: each label comes back \{label, applies, evidence\_url, quote,
- `pipeworx\_trending`: What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window \(24h, 7d, or 30d\). Useful for: \(1\) discovering what data sources are hot for current events, \(2\) confirming a popular tool is the canonical choice before asking your o
- `suggest\_questions`: What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions \(co
- `generate\_llms\_txt`: Generate a production-ready llms.txt file for any URL so AI crawlers \(ChatGPT, Claude, Perplexity\) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Us
- `ai\_visibility\_check`: Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility \(0-100\) per model. Default model is Workers AI Llama-3.3-70b \(free\); pass \`\_apiKey\` to also probe Anthropic \(BYO key — you pay Anthropic directly for those calls\). Returns per-model \{score, conf
- `scan\_competitor\_ai\_presence`: Compare AI visibility across multiple entities side-by-side. Probes each entity \(your brand + N competitors\) with ai\_visibility\_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns
- `pipeworx\_feedback`: Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data \(bug\), when a tool you wish existed isn't in the catalog \(feature/data\_gap\), or when something worked surprisingly well \(praise\). ONLY for tools served by this Pipeworx connection — if th
- `remember`: Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward \(a resolved ticker, a target address, a user preference, a research subject\) so you don't have to look it up again. Stored as a key-value pair scoped by
- `recall`: Retrieve a value previously saved via remember, or list all saved keys \(omit the key argument\). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier \(anonymous IP, BYO key hash, o
- `forget`: Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
- `current\_by\_zip`: Latest observed air quality index \(AQI\) for the EPA AirNow reporting area nearest a US ZIP code: one row per pollutant \(ozone, PM2.5, PM10\) with the AQI value, category \(Good / Moderate / Unhealthy …\), observation hour, reporting agency and yesterday's AQI for comparison. Answers "what is the air qu
- `current\_by\_location`: Latest observed air quality index \(AQI\) for the EPA AirNow reporting area nearest a latitude/longitude in the US: one row per pollutant with AQI value, category, observation hour, agency and yesterday's AQI. Answers "what is the air quality at these coordinates right now".
- `forecast\_by\_zip`: EPA AirNow air quality \(AQI\) forecast for a US ZIP code — today and up to three days ahead, per pollutant, with the forecast category, Action Day flag and the forecaster's discussion text. Pass a date \(YYYY-MM-DD\) to get one day, omit it for every day AirNow has issued. Answers "is tomorrow ok for o
- `observations\_in\_bbox`: Hourly EPA AirNow monitoring-site observations inside a bounding box for a span of UTC hours \(max 24 hours per call\): per site and hour, the AQI for ozone, PM2.5, PM10 and NO2 and the measured concentrations for PM2.5, ozone, NO2, CO, SO2 and PM10. Specify pollutants as comma-separated codes \("OZONE

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html