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 structured data with citations. Routes the question to the right one of 6,876 tools across 1811 verified sou

Parameter	Type	Required	Notes
question	string	yes	Your question or request in natural language. Accepts query, q, prompt, text, input, ask, message as aliases.
query	string	no	Alias for question.
q	string	no	Alias for question.
prompt	string	no	Alias for question.
text	string	no	Alias for question.
input	string	no	Alias for question.
ask	string	no	Alias for question.
message	string	no	Alias for question.
packs	array	no	OPTIONAL. Restrict routing to these pack slugs (e.g. ["sec-form-d","sec-13f"]) — the router then picks only from tools in those packs. Omit for the default full-catalog routing. Slugs come from list_p

Beta version of ask_pipeworx: identical universal router (same 6,876 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 matches ask_pipeworx exactly. Use it exactly like ask_pipeworx when you want the newest routing; results

Parameter	Type	Required	Notes
question	string	yes	Your question or request in natural language. Accepts query, q, prompt, text, input, ask, message as aliases.
query	string	no	Alias for question.
q	string	no	Alias for question.
prompt	string	no	Alias for question.
text	string	no	Alias for question.
input	string	no	Alias for question.
ask	string	no	Alias for question.
message	string	no	Alias for question.
packs	array	no	OPTIONAL. Restrict routing to these pack slugs (e.g. ["sec-form-d","sec-13f"]) — the router then picks only from tools in those packs. Omit for the default full-catalog routing. Slugs come from list_p

Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 6,876 across 1811 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_

Parameter	Type	Required	Notes
question	string	yes	Your question in natural language. Accepts query, q, prompt, text, input, ask, message as aliases.
query	string	no	Alias for question.
q	string	no	Alias for question.
prompt	string	no	Alias for question.
text	string	no	Alias for question.
input	string	no	Alias for question.
ask	string	no	Alias for question.
message	string	no	Alias for question.
prefer_tool	string	no	Run this exact tool instead of letting the router choose — use a name from a previous answer's alternatives[]. Arguments are still filled from your question. Unknown names are refused, never guessed.

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_within saves context, returns only the passages that matter, and every passage carries an offset so th

Parameter	Type	Required	Notes
text	string	yes	The document text to search inside (max ~200K chars).
query	string	yes	Natural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".
limit	number	no	Max passages to return (1-20, default 5).

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 1811 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web

Parameter	Type	Required	Notes
question	string	yes	The research question, in natural language. Broad/multi-part is fine — decomposition is the point. Accepts query, q, prompt, text, input, ask, message as aliases.
query	string	no	Alias for question.
q	string	no	Alias for question.
prompt	string	no	Alias for question.
text	string	no	Alias for question.
input	string	no	Alias for question.
ask	string	no	Alias for question.
message	string	no	Alias for question.
depth	string	no	How many facets to research in parallel: quick=3 (single hop), standard=3 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=6 (pai

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, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, des

Parameter	Type	Required	Notes
query	string	yes	Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as
task	string	no	Alias for query.
q	string	no	Alias for query.
description	string	no	Alias for query.
search	string	no	Alias for query.
limit	number	no	Maximum number of tools to return (default 20, max 50)

"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 FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (cross-source identity spi

Parameter	Type	Required	Notes
type	string	yes	Entity type: "company" or "drug".
value	string	yes	For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin"). Pass the ENTITY NAME ONLY — for a bond that is the ISSUER exactly as printed ("NE
country	string	no	OPTIONAL ISO 3166-1 alpha-2 of the country whose business register you mean ("NO", "FI", "JP", "GB", "FR", "EE", "BR"). Narrows the national-register fan-out and is often the difference between the ri

"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="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calend

Parameter	Type	Required	Notes
type	string	yes	Entity type: "company" or "drug".
values	array	yes	For company: 2–5 tickers/CIKs (e.g., ["AAPL","MSFT"]). For drug: 2–5 names (e.g., ["ozempic","mounjaro"]).

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), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new

Parameter	Type	Required	Notes
type	string	yes	Subscription type.
params	object	yes	Type-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. c
delivery	object	no	Optional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verif

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.

Parameter	Type	Required	Notes
id	string	yes	Subscription id (uuid) returned by subscribe.

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.

Parameter	Type	Required	Notes
include_inactive	boolean	no	Include cancelled subscriptions in the response (default false).

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 to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed

Parameter	Type	Required	Notes
type	string	no	Optional — filter to one subscription type.
since	string	no	Optional ISO timestamp — return events fired_at >= this time.
limit	number	no	Max events to return (1-200, default 50).
unread_only	boolean	no	Return only events where read_at is null (default false).
mark_read	boolean	no	Flag the returned events read in the same call (default false).

"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 SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO p

Parameter	Type	Required	Notes
type	string	yes	"company" or "ticker" — both are accepted and behave identically; value can be a ticker, CIK, or company name either way. person/place coming soon.
value	string	yes	Ticker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna"). A NAME now resolves through the national business registers as well as SEC EDGAR, so a non-US company re
country	string	no	OPTIONAL ISO 3166-1 alpha-2 of the business register you mean ("NO", "FI", "GB", "JP", "FR", "EE", "BR"). Only affects a NAME lookup, and is often what separates the company you mean from a US namesak

"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→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (

Parameter	Type	Required	Notes
type	string	yes	Entity type. Only "company" supported today.
value	string	yes	Ticker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").
since	string	yes	Window start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.

"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. Company-financial claims (revenue, net income, cash for public US companies) verify via the structured

Parameter	Type	Required	Notes
claim	string	yes	Natural-language factual claim, e.g., "Apple's FY2024 revenue was $400 billion" or "Microsoft made about $100B in profit last year".
tolerance_pct	number	no	Max percent deviation still graded approximately_correct (0.5–50). Overrides the tolerance implied by the claim wording — set 1–2 for hallucination detection where any material error must be refuted.

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 answer "the most recent figures" and will happily hand back FY2025 when you asked about FY2019, and

Parameter	Type	Required	Notes
company	string	yes	Ticker ("AAPL"), 10-digit CIK ("0000320193"), or company name. A name that matches two filers equally well returns status "ambiguous" with both named rather than guessing — pass a ticker or CIK to be
attribute	string	yes	Which figure. "revenue" = total consolidated revenue; "net_income" = net income (loss); "cash" = cash and cash equivalents at the period end.
period	object	yes	The reporting period, stated explicitly. There is no default and no "latest" — that is the point of this tool.
freshness	string	no	cached (default) permits an eligible stored answer; fresh requires an upstream refresh and never silently falls back to stale data.
max_age	number	no	Maximum age in seconds of the upstream publication, not our fetch. Older or undated facts are withheld.
as_of	string	no	Past ISO timestamp with timezone. Replay the latest answer actually recorded by that instant; no invented history or live fallback.
restatement	string	no	Default "as_amended" — the latest filed figure for the period, with everything it superseded listed. "as_originally_reported" takes the first filing instead.
basis	string	no	Only "consolidated" in v1. Segment and product-level figures are XBRL-dimensioned and are not reachable through this contract at any concept.
exclude_publishers	array	no	Publisher ids forbidden for fact retrieval: sec, fmp, alphavantage. Case and surrounding whitespace are normalized; unknown ids are refused. Excluding sec currently leaves no eligible fact source and

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 REGISTERED ENTITY and the country is not the US, or when you do not know which country it is. Registers se

Parameter	Type	Required	Notes
name	string	yes	The company name as you have it, in its own script. Pass it VERBATIM — do not strip the legal form ("Oyj", "AS", "株式会社", "Ltd"): in Japanese the form is a PREFIX as often as a suffix and 株式会社花王 and 花王
country	string	no	OPTIONAL ISO 3166-1 alpha-2 of the register you mean ("GB", "NO", "FI", "FR", "JP", "EE", "BR"). Narrows the fan-out, and is frequently the difference between an answer and ambiguous on a short name
limit	number	no	Maximum candidates to return, 1-50 (default 10). Does not change which registers are asked, only how many rivals come back.

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 does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_coun

Parameter	Type	Required	Notes
package	string	yes	npm package name. Scoped packages (e.g. "@types/node") are accepted.
version	string	no	Specific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

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 it settles, because Polymarket de-indexes resolved markets. The tool resolves the market, classifies

Parameter	Type	Required	Notes
market	string	yes	Polymarket slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), full URL ("https://polymarket.com/event/..."), or question text ("Will Bitcoin hit $150k?"). Dated slugs stop reso
depth	string	no	quick = 2-3 evidence sources, thorough = full fan-out. Default thorough.
include_raw	boolean	no	Default false. When false (recommended), FRED/FDA/GDELT/Federal-Register evidence is summarized to the few fields agents actually use — keeps responses under ~20KB. Pass true to get full upstream payl

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 for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoi

Parameter	Type	Required	Notes
event	string	no	Single-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topic	string	no	Cross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Pol

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 — crypto_price (lognormal barrier from 90d FRED log-returns) and news_momentum (GDELT 7d/21d articl

Parameter	Type	Required	Notes
window	string	no	Polymarket volume window to filter markets. Default 1wk.
limit	number	no	Top N edges to return after ranking. Default 10, max 25.
min_edge_pp	number	no	Minimum \|edge\| in percentage points to include (default 0.5). Edge is evaluated NET of slippage and Polymarket's own taker fee.
slippage_pp	number	no	Assumed execution slippage in percentage points per leg (default 0.3), for bid/ask + thin depth cost that a last-trade price does not show. Subtracted from raw \|edge\| before ranking and Kelly sizing,
category_filter	string	no	Comma-separated list to restrict the output: "model_driven" (crypto_price + news_momentum), "structural_arbitrage" (partition_overround), "concentrated_longshot". Combine like "model_driven,structural
min_kelly	number	no	Minimum half-Kelly fraction (as decimal, e.g. 0.005 = 0.5% of bankroll) to include single-leg opportunities. Default 0 (no filter). Skips opportunities that are too small to bet sensibly even if the e
min_partition_leg_kelly	number	no	Minimum BEST per-leg half-Kelly fraction across a partition_overround opportunity's top_legs (or longshot_basket legs). Default 0 (no filter). Partition arbs always return kelly_fraction_half=0 at the
min_liquidity	number	no	Tradeable-edge filter. Minimum $ liquidity on the representative market (or for partition_overround, on at least one top_leg). Default 0 (no filter). Set to 5000 to drop thin-book opportunities where
max_spread_pp	number	no	Tradeable-edge filter. Maximum bid/ask spread in percentage points on the representative market. Default null (no filter). Set to 2 to require tight books — anything wider eats most plausible edges.

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) topic — 11 pre-mapped macro subjects ("fed", "btc", "eth", "cpi", "gdp", "sp500", "recession", "next

Parameter	Type	Required	Notes
topic	string	no	Subject to compare. Canonical keys: fed \| btc \| eth \| cpi \| gdp \| sp500 \| recession \| next_pope \| next_uk_pm \| next_israel_pm \| 2028_president — but aliases and keywords resolve too ("bitcoin", "fed r
kalshi_event_ticker	string	no	Explicit Kalshi event ticker, e.g. "KXFED-26OCT". Overrides the topic-mapped Kalshi side.
polymarket_event_slug	string	no	Explicit Polymarket event slug, e.g. "fed-decision-in-june-825". Overrides the topic-mapped Polymarket side.

Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of market (single-market mode) or event (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shar

Parameter	Type	Required	Notes
market	string	no	Single-market mode: market slug or full polymarket.com URL.
event	string	no	Basket mode: event slug or full polymarket.com URL — checks every leg of the partition.
side	string	no	Single-market: buy_yes \| sell_yes \| buy_no \| sell_no (default buy_yes). Basket: sell_yes \| buy_yes (default auto — sell if partition sum > 1, buy if < 1).
size_usd	number	no	Single-market: USD to spend (buys) or target proceeds (sells). Basket: settlement notional — shares per leg, each paying $1 at resolution. Default 1000, clamp 10–1,000,000.

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, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in

Parameter	Type	Required	Notes
days	number	no	Lookback in days (default 14, clamp 2-30).
window	string	no	Which polymarket_edges window family to read snapshots for: 24hr \| 1wk \| 1mo (default 1wk).

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_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (backtest_days: N): score

Parameter	Type	Required	Notes
city	string	no	City to price, e.g. "nyc", "chicago", "los angeles", "miami", "austin", "houston", "denver", "philadelphia". Defaults to nyc. Unmapped cities return known_cities[] rather than a wrong series.
series_ticker	string	no	Explicit Kalshi series, e.g. "KXHIGHNY" or "KXHIGHTBOS" (Boston). Overrides city; use it for any of the 121 daily weather series not in the city list.
date	string	no	Settlement date as YYYY-MM-DD. Defaults to the soonest open event. Daily weather markets open ~1-2 days ahead and close 05:00Z the next day.
market_type	string	no	"high_temp" (default) \| "precip". Precipitation markets return prices but no forecast_prob yet.
backtest_days	number	no	Run measurement mode over the last N settled days (max 60) instead of pricing today. Returns brier_market vs brier_forecast, the settlement-vs-forecast basis, and per-day detail. Both sides are scored

Extract the settlement clause of a single Polymarket or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at, the precision of the computation (e.g. "1-minute candle close" vs "60-second trailing average" vs "election outcome"), the evidence standard (official_source | consensus_reporting | any_credible_report | unspecified), and void_handling (cancel

Parameter	Type	Required	Notes
venue	string	yes	Which venue to fetch the market from.
market	string	yes	Polymarket market slug or URL, OR a Kalshi market ticker (preferred) or event ticker (falls back to a representative market under that event).

Field-by-field diff of TWO markets' settlement clauses (one from each of a and b; either can be Polymarket or Kalshi) — runs resolution_audit on both sides and compares source, settle time, precision, and evidence standard. Returns equivalent: "true" only when both sides parsed with enough confidence to compare AND no field conflicts; "false" when a specific conflict was found (differing_fie

Parameter	Type	Required	Notes
a	object	yes	First market to compare.
b	object	yes	Second market to compare.

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 other pack (≤ 60s TTL) and there is no push/webhook — do not use this to try to beat a release, use it

Parameter	Type	Required	Notes
hours	number	no	Look-ahead window in hours from now. Default 48. Capped at 720 (30 days) — econ/fed releases are dated weeks apart, so a short window is often empty; widen rather than assume nothing is scheduled.
categories	string	no	Comma or space separated subset of econ\|fed\|fda\|sec\|court, or "all" (default). E.g. "econ,fed" or "fda".

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 between the date asked for and the capture actually used (e.g. "Captured 1.5 day(s) before the requested d

Parameter	Type	Required	Notes
url	string	yes	The page address, e.g. "https://www.sec.gov" or "https://www.ftc.gov/policy-notices/privacy-policy".
date	string	yes	The date to look up, as YYYY-MM-DD (e.g. "2023-06-01"), YYYYMMDD, or a full ISO timestamp.
max_gap_days	number	no	Furthest a capture may be from the date and still be used, in days. Default 30, max 3650.
max_chars	number	no	Characters of page text to return. Default 12000, max 60000.

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 timestamps with their gaps from the requested dates. It diffs readable text, not markup, so a restyled page

Parameter	Type	Required	Notes
url	string	yes	The page address, e.g. "https://www.ftc.gov/policy-notices/privacy-policy".
date_a	string	yes	The earlier date, as YYYY-MM-DD (e.g. "2021-06-01").
date_b	string	yes	The later date, as YYYY-MM-DD (e.g. "2024-06-01").
max_gap_days	number	no	Furthest a capture may be from each date and still be used, in days. Default 30, max 3650.

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 the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was gi

Parameter	Type	Required	Notes
entity	object	yes	The row/company to research. At least one of name/domain required.
question	string	yes	The question to answer about this company, in natural language, e.g. "Does this company sell to healthcare, and who is the head of sales?"
output_schema	object	yes	JSON Schema object naming the fields to extract, e.g. {"properties":{"sells_to_healthcare":{"type":"boolean"},"head_of_sales":{"type":"string"}}}. Up to 20 fields.
sources	string	no	Where to look: "web" (company site only), "catalog" (entity_profile only), "both" (default).
max_cost	number	no	Cost ceiling in US dollars for this one row. Default 0.02, max 0.50, minimum viable 0.002 (below that the call is refused rather than silently exceeding it).

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, status: found|inferred|not_established} — "found" only when the model's quote is independently verif

Parameter	Type	Required	Notes
entity	object	yes	The row/company to classify. At least one of name/domain required.
labels	array	yes	Candidate labels to test, 2-30 strings, e.g. ["healthcare","fintech","logistics"].
text	string	no	Text to classify directly (a description, a page you already fetched, etc.) — cheapest path, skips any fetch.

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 own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating si

Parameter	Type	Required	Notes
window	string	no	24h (default) \| 7d \| 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

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 (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, gove

Parameter	Type	Required	Notes
topic	string	no	Optional focus area: finance \| pharma \| economics \| real-estate \| betting \| weather \| government \| science \| news. Omit for a cross-category spread.

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. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing

Parameter	Type	Required	Notes
url	string	yes	Full URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_links	number	no	Maximum number of link entries to include (default 25, max 50).

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, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand c

Parameter	Type	Required	Notes
entity	string	yes	The thing to ask about. Brand/business name, product name, person, or topic. E.g. "Pipeworx", "OpenInvoice", "Acme Corp pricing".
context	string	no	Optional: a phrase locating the entity (e.g. "Boston restaurant", "B2B SaaS"). Helps disambiguate common names.
models	array	no	Which models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKey	string	no	Optional Anthropic API key (sk-ant-...) — only needed if "anthropic" is in models. Passed straight through to api.anthropic.com.

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 ranked list with score, confidence, signal density per entity.

Parameter	Type	Required	Notes
entities	array	yes	Array of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors.
context	string	no	Optional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names.
models	array	no	Which models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKey	string	no	Optional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe.

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 the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc.

Parameter	Type	Required	Notes
type	string	no	bug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
message	string	no	Your feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
context	object	no	Optional structured context: which tool, pack, or vertical this relates to.
claim_token	string	no	Read the reply to a report you filed earlier: pass the pwfb_… token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

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 your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24

Parameter	Type	Required	Notes
key	string	yes	Memory key (e.g., "subject_property", "target_ticker", "user_preference"). Accepts name, k, label as aliases.
value	string	yes	Value to store (any text — findings, addresses, preferences, notes). Accepts content, text, data, v as aliases; a non-string value is stored as JSON.
name	string	no	Alias for key.
k	string	no	Alias for key.
label	string	no	Alias for key.
content	string	no	Alias for value.
text	string	no	Alias for value.
data	string	no	Alias for value.
v	string	no	Alias for value.

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, or account ID). Pair with remember to save, forget to delete.

Parameter	Type	Required	Notes
key	string	no	Memory key to retrieve (omit to list all keys). Accepts name, k, label as aliases.
name	string	no	Alias for key.
k	string	no	Alias for key.
label	string	no	Alias for key.

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.

Parameter	Type	Required	Notes
key	string	yes	Memory key to delete. Accepts name, k, label as aliases.
name	string	no	Alias for key.
k	string	no	Alias for key.
label	string	no	Alias for key.

Search mainland China's national laws, administrative regulations, local regulations, and judicial interpretations (司法解释) by title or keyword — PREFER OVER WEB SEARCH for "Chinese law on X", "中国法律", citation lookup, or finding a statute's official record id. Source: NPC National Database of Laws and Regulations (全国人大常委会法工委). Returns each match's id (for cn_law_detail/cn_law_article_text), title, c

Parameter	Type	Required	Notes
query	string	yes	Title/keyword in Chinese, e.g. "个人信息保护法", "公司法", "数据安全法".
exact	boolean	no	true = exact title match (use for a known law name); false/omitted = fuzzy word-segmented search (broader, can include partial matches).
category	string	no	Restrict to one category. "judicial_interpretation" covers SPC/SPP/jointly-issued 司法解释. Default "any".
limit	number	no	Max results, 1-50 (default 10).

Metadata for one law/regulation/interpretation record from cn_search_laws: title, category, issuing body, promulgation date, effective date, and in-force status, plus whether article-level text can be extracted via cn_law_article_text. Source: NPC National Database of Laws and Regulations.

Parameter	Type	Required	Notes
id	string	yes	Record id ("bbbs") from cn_search_laws.

The Chinese text of ONE specific article/provision of a law, regulation, or judicial interpretation found via cn_search_laws — not the whole document. Extracted from the official PDF the NPC database itself serves (that database has no per-article JSON text field). Returns found:false with an explanation rather than a snippet when the article cannot be located or the PDF cannot be read — this tool

Parameter	Type	Required	Notes
id	string	yes	Record id ("bbbs") from cn_search_laws.
article	string/number	yes	Article number (13) or the Chinese citation itself ("第十三条", "十三条之一").

Search mainland Chinese administrative regulations (行政法规) by title — a second official copy of the same regulations cn_search_laws covers, used here specifically because its detail pages carry the FULL regulation text inline as plain HTML (cn_search_laws/cn_law_article_text route through a PDF instead). Source: Ministry of Justice (司法部), National Administrative Regulations Database.

Parameter	Type	Required	Notes
query	string	yes	Title keyword in Chinese, e.g. "公司法" (matches implementing regulations), "数据安全".
limit	number	no	Max results, 1-30 (default 10).

Full Chinese text of one administrative regulation found via cn_search_admin_regulations, plus its revision-date history. Source: Ministry of Justice, National Administrative Regulations Database.

Parameter	Type	Required	Notes
law_id	string	yes	Record id ("LawID") from cn_search_admin_regulations.

Index of the Supreme People's Court's official Guiding Cases (指导性案例) — binding case guidance for lower courts, numbered sequentially and released in batches. Page 1 is the newest batch. Source: court.gov.cn, 审判业务 > 指导性案例.

Parameter	Type	Required	Notes
page	number	no	Page number, 1 = newest (default 1). Higher numbers go further back.

Full text of one Supreme People's Court Guiding Case from cn_guiding_cases_list: title, issuing source, publication date, keywords (关键词), holding (裁判要点), and the full case narrative, in Chinese. Source: court.gov.cn.

Parameter	Type	Required	Notes
id	string	yes	Case id from cn_guiding_cases_list.

Where are you running it?

Tool surface

Release history

Cn Law MCP

What it does

Quickstart

Where are you running it?

Tool surface

What counts against your monthly calls

Release history

See also