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Stocklake — AI Stock Intelligence

Get Stock

get_stock
Read-onlyIdempotent

Price, fundamentals, technical indicators, and company profile for a stock. Returns all data needed to understand a stock in a single call.

Key fields:

  • price, change_pct, prev_close, week52_high/low, volume, avg_volume

  • market_cap, enterprise_value, beta

  • pe_trailing, pe_forward, price_to_book, dividend_yield, dividend_rate

  • debt_to_equity, profit_margins, operating_margins, gross_margins, return_on_equity, free_cashflow

  • revenue_growth, earnings_growth, revenue_ttm, gross_profit_ttm

  • analyst_rating: "strong_buy"|"buy"|"hold"|"sell"|"strong_sell" (analyst consensus)

  • analyst_rating_score: 1.0-5.0 mean analyst recommendation (1=strong_buy, 5=strong_sell)

  • analyst_target: mean analyst price target

  • analyst_count: number of analyst opinions

  • indicators: raw RSI, MACD, Bollinger Bands, SMA20/SMA200 (the canonical 50/200-day averages -- no separate top-level ma_50/ma_200 field), EMA20/EMA200, ATR

  • description: company business description

  • website, employees, officers (top 5: name, title, total_pay)

  • updated_at: last data sync timestamp Available to all tiers (raw indicator numbers, no interpretation). This basic six (RSI/MACD/Bollinger/SMA/EMA/ATR) is standard, widely-available technical analysis.

Pro tier also unlocks the specialized indicators inside the SAME indicators block: williams_r, ultimate_osc, vix_fix, williams_ad (the Larry Williams family), td_sequential (DeMark), elliott_wave, adx {adx, plus_di, minus_di}, ichimoku {tenkan, kijun, cloud_top, cloud_bot, above_cloud, below_cloud}, squeeze {squeeze_on, hist}, and rs_rank (relative-strength rank 1-99, stocks only: the past year's return with the latest quarter counted double, ranked against every tracked stock; 99 = strongest; absent with under a year of history). These are omitted entirely from the free/guest response, not merely unlabeled; free/guest calls get indicators with only the basic six populated.

Pro tier adds four interpreted blocks computed from the same indicators, no extra AI cost, plus a minimum AI-narrative slice - all five below are precomputed, none cost a live AI call:

  • ai_verdict / ai_headline / ai_score / ai_score_band: the minimum useful AI-narrative slice, shared by every pro-tier stock-returning tool. A bare verdict alone isn't actionable (e.g. bearish while up 8% on the day with a strong_buy analyst rating is genuinely ambiguous) - the one-line headline is the "why", ai_score is the 0-100 composite (same scale/band convention as get_signals' signal_score, distinct pipeline). For the full text (summary/key_points/risks/near_term/longer_term) and cross-source news/insider context, call get_stock_research(symbol) instead - that's the only tool with the complete bundle.

  • ai_score (0-100) / ai_score_band (Weak/Moderate/Strong/Very Strong): the AI research composite score, on the same 0-100 scale and band boundaries as get_signals()'s signal_score - but a separate score, never the same number for the same symbol by coincidence alone.

  • rating: {score 0-10, direction POSITIVE/NEUTRAL/NEGATIVE, signals per-indicator breakdown}

    • composite technical score

  • signals: flat labeled signals (rsi/macd/bollinger/sma200/sma50/williams_r/ultimate_osc/ vix_fix/williams_ad/td_sequential/elliott_wave, each with a value + plain-English label)

    • same indicators as 'indicators', pre-interpreted for programmatic use without parsing raw numbers

  • stance_signals: unified list of per-source directional calls (technical rating, AI summary near_term/longer_term, insider/institutional sentiment, analyst consensus, active screener signals) - each entry {stance POSITIVE/NEGATIVE/NEUTRAL, conviction 0-10, horizon INTRADAY/SWING/POSITION/LONG_TERM, edge_quality PROVEN/OBSERVATION/UNKNOWN (per-source signal_backtest track record), source, raw_label, as_of}. Same canonical shape used on the stock detail page - a source with missing/stale data is simply omitted, not nulled out.

  • relative_strength: {windows: {5d/20d/60d/120d/12m -> {stock_return_pct, rs_vs_spy, rs_vs_qqq, rs_vs_sector}}, verdict: one-line plain-language read (e.g. "Laggard - weak near- and long-term")}

    • stock's own return minus each benchmark's return (percentage points, not a ratio) per window. rs_vs_sector uses the stock's GICS sector SPDR ETF (Vanguard backup if the primary lacks history); omitted for stocks with no resolvable sector (crypto, FX, indices). Windows/ benchmarks with insufficient history are omitted rather than null. null if not precomputed yet.

  • market_risk: {beta_spy_1y, corr_spy_1y} - 1-year daily-return beta and correlation vs SPY. Distinct from quote.beta (a longer-window beta) - this is computed from the same daily bars as relative_strength. Both fields null if not yet precomputed for this symbol (populates on the next scheduled indicators run).

  • forensic_scores: {altman_z, piotroski_f, beneish_m, computed_at} - three classic forensic- accounting formulas (Altman 1968 bankruptcy-risk, Piotroski 2000 fundamental-strength, Beneish 1999 earnings-manipulation-likelihood), computed from balance sheet/income statement/cash flow data, refreshed on each company's own filing cadence (roughly annual). Each sub-block is {score, note, ...} - altman_z adds zone (safe/grey/distress), piotroski_f adds strength (strong/moderate/weak, 0-9 scale), beneish_m adds likely_manipulator (bool, score > -1.78). note explains what the score measures and its known caveats (e.g. Altman Z is not meaningful for banks/insurers and can flag REITs/ client-float businesses as "distress" by design) - always read alongside the score, not in isolation. score: null means genuinely not computable for this company (common for financial-sector names), not an error. No trading signal is derived from these scores anywhere in this API today - treat as raw accounting-model output for your own research.

  • sector_context: where this stock's fundamentals sit versus the other tracked equities in its own sector - {sector, revenue_growth, gross_margin, operating_margin, as_of}, each metric {value, sector_median, percentile 0-100, n}. Purely descriptive positioning (e.g. "revenue growth is in the 80th percentile of its sector"), no interpretation or direction. A metric is omitted when the stock has no value for it or the sector has fewer than 15 peers with data; the whole block is omitted when nothing is computable. Baseline refreshed daily; sectors are pooled globally across all tracked equities. get_stock also returns trend: {period: "quarterly", points: [{period_end, revenue_growth / gross_margin / operating_margin: {value, sector_median, n}}]}, oldest first - the same three metrics for the last few quarters (revenue_growth is year-over-year) beside the sector median for each quarter, so you can see whether the stock is gaining or losing ground on its peers. Off-cycle fiscal quarters are matched to the nearest calendar quarter. A quarter or metric is left out where either side lacks data. get_stocks omits trend to keep batch rows small.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol. Also accepts a company name as a fallback (e.g. "Apple") when it uniquely resolves to one symbol.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / symbol / description
      Added value: +"Stock ticker symbol. Also accepts a company name as a fallback (e.g. \"Apple\") when it uniquely resolves to one symbol."
  2. First observed

TDQS

Score is being calculated.

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