"StockX" matching MCP tools:

• pipeworx_feedback

  China Stocks

  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). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• get_market_assessment

  Stocklake — AI Stock Intelligence

  Combined AI market assessment: macro regime + market outlook in a single call. Produced every ~4 hours by the market intelligence pipeline. Two distinct perspectives returned together: - REGIME (RISK_OFF/CAUTIOUS/NEUTRAL/AGGRESSIVE): answers "how much equity risk to take" → use for position sizing and asset allocation decisions - OUTLOOK (BULLISH/NEUTRAL/BEARISH): answers "which direction and sectors to trade" → use for sector preference and directional bias Both share the same pipeline run so they are always in sync. - history_count: include last N prior assessments for each (0-3, default 0) - regime_*: risk posture fields — regime, regime_bias, regime_confidence, regime_rationale, key_risks, watch_for, vix_at_assessment, regime_updated_at - indicators.macro_data: FRED macro data (yield curve, Fed funds, cpi_index, unemployment, M2) - indicators.volatility_term_structure: VIX spot/3M/6M term structure + contango signal - indicators.market_sentiment: CNN Fear & Greed value and label - market_context: price/RSI/SMA200/perf snapshot of SPY/QQQ/IWM/TLT/GLD/VIX/TNX + sectors NOTE: point-in-time snapshot recorded when AI ran — not live prices (use get_market_pulse for live) - outlook_*: directional fields — outlook, outlook_conviction, equity_view, preferred_sectors, avoided_sectors, catalyst, outlook_key_risk, outlook_rationale, outlook_updated_at Pro tier only — AI pipeline cost attached. For informational purposes only. Not financial advice.

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• batch_quote

  Stock Market Data MCP

  Get latest quotes for many tickers in one call — price, change, volume, market cap, P/E and 52-week range for each. FREE for up to 10 tickers. Above 10, PAID at $0.005 USDC per extra ticker after the daily free allowance (cap 100 tickers). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.

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• deep_research

  China Stocks

  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 1353 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,139 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).

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• compare_entities

  China Stocks

  "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-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

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• recent_changes

  China Stocks

  "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 (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

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• polymarket_arbitrage

  China Stocks

  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-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

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• polymarket_fill_risk

  China Stocks

  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, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

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• remember

  China Stocks

  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 hours. Pair with recall to retrieve later, forget to delete.

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• recall

  China Stocks

  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.

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• get_earnings_calendar

  Stocklake — AI Stock Intelligence

  Upcoming earnings dates for stocks in the Stocklake universe. - days: look-ahead window in days (default 7, max 30) - Returns: { window_days, from_date, to_date, count, results[] } - Each result: symbol, name, sector, market_cap, price, rsi, earnings_date (ISO UTC), is_estimate, eps_trailing, eps_forward - Sorted by earnings_date ascending. - Dates sourced from market data — treat is_estimate=true dates as approximate. Available to all tiers.

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• get_news_feed

  Stocklake — AI Stock Intelligence

  Top AI-flagged news across all tracked stocks — the market-wide news briefing. Unlike get_stock_news (per-symbol), this scans the entire universe and returns the most notable articles ranked by AI flag score, newest first within each score tier. Use this for: - Morning briefing: "what happened in the market this week?" - Catalyst scanning: "what news is driving moves right now?" - Event monitoring: "which stocks have high-impact news today?" - min_flag_score: minimum AI flag score (default 8, min 5, max 10) 8 = notable · 9 = high-impact · 10 = exceptional - days: look-back window in days (default 3, max 10) - limit: max articles returned (default 10, max 25) - Per article: symbol, title, published_at, ai_sentiment, ai_flag_score (0-10), ai_summary (full text), ai_confidence (0-10) Pro tier only — AI pipeline cost attached. For informational purposes only. Not financial advice.

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• screener

  Stock Market Data MCP

  Screen the tracked large-cap universe by market cap, trailing P/E, dividend yield, and sector — returns matching stocks ranked by market cap. A raw market-data filter; for a ranked, fundamentals-driven screen pair this with financial-signals-mcp's composite_value_score. PAID: $0.01 USDC per query after a daily free allowance. On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.

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• entity_profile

  China Stocks

  "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, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

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• scan_dependency

  China Stocks

  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_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

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• ashares_quote

  China Stocks

  Real-time quote(s) for Chinese A-share stocks by 6-digit code (Shanghai 6xxxxx, Shenzhen 0xxxxx/3xxxxx, STAR 688xxx, ChiNext 30xxxx, Beijing 8xxxxx/4xxxxx). Returns name, current price, change and change %, open, previous close, day high/low, volume, turnover, and the quote timestamp. Accepts one code or a comma-separated list. Example: ashares_quote({ symbols: "600519,000858" }) for Kweichow Moutai and Wuliangye. Source: Sina (keyless).

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• get_stocks

  Stocklake — AI Stock Intelligence

  Batch stock data for up to 50 symbols in a single call. Returns a dict keyed by symbol. Missing symbols are omitted from the result. Each symbol in the batch counts as one call toward the daily limit. Available to all tiers.

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• get_news_feed

  Stocklake — AI Stock Intelligence

  Top AI-flagged news across all tracked stocks — the market-wide news briefing. Unlike get_stock_news (per-symbol), this scans the entire universe and returns the most notable articles ranked by AI flag score, newest first within each score tier. Use this for: - Morning briefing: "what happened in the market this week?" - Catalyst scanning: "what news is driving moves right now?" - Event monitoring: "which stocks have high-impact news today?" - min_flag_score: minimum AI flag score (default 8, min 5, max 10) 8 = notable · 9 = high-impact · 10 = exceptional - days: look-back window in days (default 3, max 10) - limit: max articles returned (default 10, max 25) - Per article: symbol, title, published_at, ai_sentiment, ai_flag_score (0-10), ai_summary (full text), ai_confidence (0-10) Pro tier only — AI pipeline cost attached. For informational purposes only. Not financial advice.

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• get_indicator_history

  Stocklake — AI Stock Intelligence

  Historical daily indicator snapshots for a stock — ideal for charting and trend detection. Returns up to `days` days of data (max 730, default 90) from the stock_indicator_snapshots collection which is populated daily by the indicator pipeline. Each snapshot row contains: - recorded_at: ISO date string - price: closing price at snapshot time - rsi: RSI(14) value (0-100) - macd_histogram: MACD histogram value (positive = bullish momentum) - bb_pct: Bollinger Band % position (0 = at lower, 100 = at upper band) - sma20 / sma200: 20-day and 200-day simple moving averages - williams_r: Williams %R (0 to -100; >-20 overbought, <-80 oversold) - ultimate_osc: Ultimate Oscillator (0-100; >70 overbought, <30 oversold) - vix_fix_value: Williams VIX Fix synthetic fear gauge (higher = more fear) - williams_ad_trend: Accumulation/Distribution trend (rising/falling/flat) - td_signal: DeMark TD Sequential signal (BUY_SETUP/SELL_SETUP/BUY_COUNTDOWN/SELL_COUNTDOWN/null) - td_phase: DeMark phase (setup_active/setup_complete/countdown_active/countdown_done/null) - analyst_rating: analyst consensus (buy/outperform/hold/underperform/sell or null) - analyst_target: mean analyst price target or null Returns {} if fewer than 3 snapshots found. Pro tier only. For informational purposes only. Not financial advice.

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• options_chain

  Stock Market Data MCP

  Get the option chain for a ticker — calls and puts with strike, last price, bid/ask, volume, open interest, and implied volatility, plus the available expiries. (Greeks are not provided by the source; IV/OI/volume are.) PAID: $0.02 USDC per query after a daily free allowance. On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.

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