Tearsheet Pro: Stock Fundamentals API for AI Trading Agents

Give your trading agent the full fundamental picture of any listed company in one tool call: 2,119 data points for 30,000+ stocks across 126 countries, returned as one structured JSON object.

Financial statements (5 fiscal years + latest quarter), consensus estimates to FY+3, valuation multiples, growth and CAGR, leverage, ownership, business and geographic segments, comparable companies, recent headlines, and 260 days of daily prices and volumes. Use it as an MCP tool, a LangChain / CrewAI / TradingAgents tool, or a plain REST call.

No data-vendor subscription and no monthly minimum: you pay per company returned, and invalid tickers cost nothing.

Built for AI trading agents

An agent that assembles a company profile from 10-15 separate endpoints burns tokens, latency and tool-call budget before it starts reasoning. Tearsheet Pro returns everything in one response, with the same snake_case field names for Apple, Toyota, Samsung or Saudi Aramco, so one prompt works for every market.

• Fits in one context window. A full profile is about 21K tokens of JSON (measured on Broadcom). The four statement sections are about half of that; drop daily_prices / daily_volumes client-side when your agent only needs fundamentals.
• Units an LLM can't misread. Values carry their unit: "USD 346.25" (per share), "USD 1652869.34m" (millions), "36.61x" (multiples), "43.98%" (percent). Period suffixes are explicit: _fy_4 ... _fy0, _ltm, _q0, _fyplus1e ... _fyplus3e.
• One schema across 126 countries. No per-exchange adapters and no switching providers when your agent screens Japan, India or the Gulf.
• Any currency, converted at the source. Get every value (statements, prices, estimates, segments) in USD, EUR or 30+ other currencies, or in each company's reporting currency, at historical or current FX rates. Compare Toyota, Samsung and Broadcom in one currency without your own FX table.
• Predictable cost per decision. $0.05 per company from cache, $0.25 for a live refresh. A 100-stock universe refreshed from cache costs about $5.

Agent roles it feeds

Agent role	Sections it uses
Fundamentals analyst	income_statement, balance_sheet, cash_flow, ratios, derived_metrics
Valuation / relative value	valuation_multiples, avg_multiples_3yr, comparable_companies
Growth / momentum	growth_yoy, cagr_3yr, cagr_5yr, estimates, daily_prices, daily_volumes
Risk manager	leverage_multiples, capital_structure, market_data (beta, short interest, 52-week range)
Sentiment / news	news, ownership (top 10 institutional holders)

This maps directly onto the analyst team in TradingAgents and similar multi-agent frameworks.

Connect your agent

You need an Apify API token. Nothing else.

As an MCP tool (Claude, Cursor, any MCP client)

Apify's hosted MCP server exposes this actor as a tool:

{
  "mcpServers": {
    "tearsheet-pro": {
      "url": "https://mcp.apify.com/?actors=workhard3000/tearsheet-pro",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Or run it locally: npx -y @apify/actors-mcp-server --actors workhard3000/tearsheet-pro with APIFY_TOKEN set.

Python (apify-client)

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("workhard3000/tearsheet-pro").call(run_input={
    "companies": [
        {"country": "United States", "ticker": "NVDA"},
        {"country": "Taiwan", "ticker": "2330"},
    ]
})
for profile in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(profile["ticker"], profile["valuation_multiples"])

LangChain

from langchain_apify import ApifyActorsTool

tearsheet = ApifyActorsTool("workhard3000/tearsheet-pro")  # reads APIFY_API_TOKEN
# add `tearsheet` to your agent's tools

REST (one synchronous call)

$curl -X POST "https://api.apify.com/v2/acts/workhard3000~tearsheet-pro/run-sync-get-dataset-items?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"companies": [{"country": "United States", "ticker": "NVDA"}]}'

Cached companies return in a few seconds; a live refresh takes about 2 minutes.

Why Tearsheet Pro

One call replaces dozens of API requests

Most financial data providers force you to stitch together separate endpoints for statements, ratios, estimates, prices, ownership, and segments. Tearsheet Pro returns everything in one response, organized into 23 structured sections. No pagination. No data assembly required.

Global coverage, not just US stocks

While most financial data APIs cover US tickers only, Tearsheet Pro spans 126 countries, from the NYSE to the Tokyo Stock Exchange, Bombay Stock Exchange, Shanghai, London, Frankfurt, and dozens of emerging markets. Screen 6,000+ Chinese companies, 2,600+ Japanese companies, or 1,900+ Indian companies, all from the same interface.

Pay only for what you use

No monthly minimum. No annual contract. You pay per result, and wrong tickers cost nothing.

How it compares

Feature	Tearsheet Pro	Bloomberg Terminal	Refinitiv Eikon	Financial Datasets API
Annual cost (typical)	$50-500/yr	$24,000/yr/seat	$22,000/yr/seat	$2,400/yr
Pricing model	Pay per result	Annual license	Annual license	Monthly subscription
Companies covered	30,000+ global	~50,000 global	~40,000 global	27,000 US only
Countries	126	100+	100+	1 (US)
Data points per company	2,119	Varies	Varies	Requires many calls
Single-call profile	Yes	No (terminal UI)	No (terminal UI)	No (per-endpoint)
Currencies	30+	100+	100+	USD only
Forward estimates	FY+1E to FY+3E	Yes	Yes	No
Comparable companies	Yes	Yes	Yes	No
Segments (business/geo)	Yes	Yes	Yes	Limited
No code required	Yes (Apify UI)	No	No	No

Pricing

Pay-per-event pricing. You pay only for results delivered.

Event	Price	When charged
Cached result	$0.05	Per company returned from cache (< 30 days old)
Fresh result	$0.25	Per company refreshed live (new or forced refresh)

Example costs:

Scenario	Est. cost
1 company (cached)	$0.06
10 companies (cached)	$0.51
1 company (fresh)	$0.26
5 fresh + 5 cached	$1.51
Full FAANG profile (5 companies, cached)	$0.26
100 companies/month (all cached)	~$5.01

Invalid tickers or mismatched countries are never charged.

How it works

1. Add companies: add one or more companies, each with its own country and ticker
2. Smart cache: if data is < 30 days old, it returns instantly (~3 seconds)
3. Live refresh: cache misses trigger an on-demand data pull (~2 minutes)
4. Force refresh: override the cache to get the freshest data available

23 data sections in every company profile

#	Section	Fields	What you get
1	company	16	Ticker, name, description, exchange, country, sector, industry, employees
2	market_data	29	Stock price, 52-week high/low, beta, dividends, YTD performance
3	capital_structure	19	Shares outstanding, market cap, enterprise value, total debt
4	leverage_multiples	14	EBITDA/Interest, Debt/EBITDA, Net Debt/EBITDA ratios
5	estimates	30	Consensus estimates: Revenue, EBITDA, EPS, CapEx (FY+1E to FY+3E)
6	valuation_multiples	72	TEV/Revenue, TEV/EBITDA, P/E, P/BV across FY-4 to FY+2E
7	avg_multiples_3yr	12	3-year average TEV/Revenue, TEV/EBITDA, P/E, P/CF
8	growth_yoy	78	Year-over-year growth: Revenue, EBITDA, Net Income, EPS
9	cagr_3yr	44	3-year compound annual growth rates
10	cagr_5yr	66	5-year compound annual growth rates
11	balance_sheet	253	Assets, liabilities, equity from FY-4 to latest quarter
12	income_statement	253	Revenue through net income from FY-4 to latest quarter
13	cash_flow	198	Operating, investing, financing flows from FY-4 to latest quarter
14	ratios	242	Margins, returns, turnover, leverage across FY-4 to latest quarter
15	forward_ratios	8	Forward revenue growth, EBITDA margin, net income margin
16	derived_metrics	165	Free cash flow, unlevered FCF, FCF yield, margin analysis
17	business_segments	20	Top 10 business segments with revenue breakdown
18	geographic_segments	20	Top 10 geographic segments with revenue breakdown
19	ownership	30	Top 10 institutional holders with shares and percentage
20	comparable_companies	10	Top 10 comparable company tickers
21	news	20	5 most recent headlines with dates and URLs
22	daily_prices	260	Daily closing prices for the last 260 trading days
23	daily_volumes	260	Daily trading volumes for the last 260 trading days

Total: 2,119 structured data points per company.

Coverage

• 30,000+ companies across 126 countries and all major exchanges
• Top markets: China (6,057), United States (3,830), Japan (2,668), India (1,994), Taiwan (1,754), South Korea (1,553), Canada (812), Hong Kong (663), Australia (637), United Kingdom (570)
• 30+ output currencies including USD, EUR, GBP, JPY, CNY, and local reporting currency
• 5 fiscal years + latest quarter of financial statement history
• Forward consensus estimates for FY+1E, FY+2E, and FY+3E

Use cases

LLM trading agents and autonomous research Give your AI agent a complete financial toolkit. Feed TradingAgents, LangChain agents, or custom LLM pipelines with 2,119 structured data points per company. Your Fundamentals Analyst agent gets balance sheets, income statements, and growth rates. Your Risk Manager gets leverage ratios, debt structure, and liquidity metrics. All from one call.

RAG and financial knowledge bases Index Tearsheet Pro output into Pinecone, Weaviate, or Chroma. Let your LLM answer questions like "Which FAANG company has the highest free cash flow yield?" using real data instead of training cutoff snapshots.

Equity research and investment analysis Generate a complete tearsheet for any company. Compare Apple's valuation multiples against the semiconductor industry. Screen all 1,994 Indian companies for undervalued mid-caps. Pull Toyota's financials in EUR for a European investor presentation.

Portfolio monitoring Track balance sheet health, growth rates, and valuation changes across your holdings. Run weekly refreshes on 50 portfolio companies for under $3/month.

Sector and country screening Browse all 6,057 Chinese companies, filter by industry, and compare growth rates. Identify the fastest-growing companies in Southeast Asia. Map the entire Saudi Arabian stock market.

Quantitative models and backtesting Feed structured JSON into trading models. Every field uses consistent snake_case naming across all 30,000+ companies. 260 days of daily prices included for momentum signals.

M&A due diligence Pull comprehensive profiles for acquisition targets and comparable companies. Business segments, geographic breakdowns, ownership structure, and capital structure all in one response.

Cross-border company comparison Compare Samsung (Korea), TSMC (Taiwan), and Intel (US) side-by-side in USD. Tearsheet Pro resolves tickers across exchanges automatically.

Input

Field	Type	Default	Description
companies	array	(none)	Array of companies to fetch. Each entry has country, ticker, and optional companyName.
currency	select	USD	Reporting currency (30+ options)
fxConversion	select	Historical	Currency conversion method
estimateConsolidation	select	Consolidated	Consolidation type
forceRefresh	boolean	false	Force a fresh pull regardless of cache

Each company in the companies array can have a different country. This lets you mix tickers from any market in a single run:

{
  "companies": [
    { "country": "United States", "ticker": "AAPL" },
    { "country": "Japan", "ticker": "7203" },
    { "country": "South Korea", "ticker": "A005930" }
  ],
  "currency": "USD"
}

Output

Each result contains the ticker, company name, data source, cache age, and all 23 sections as nested JSON objects. Excerpt from a real Broadcom (AVGO) result:

{
  "ticker": "AVGO",
  "company_name": "Broadcom Inc.",
  "currency": "USD",
  "source": "cache",
  "age_days": 10,
  "company": { "exchange": "NasdaqGS", "country": "United States", "primary_industry": "Semiconductors", "employees": 33000, ... },
  "market_data": { "mkt_share_price": "USD 346.25", "mkt_market_capitalization": "USD 1652869.34m", "mkt_5_year_beta": 1.48, ... },
  "income_statement": { "is_total_revenues_fy_1": "USD 51574m", ... },
  "estimates": { "est_revenue_est_fyplus1e": "USD 105972.84m", "est_eps_est_fyplus1e": "USD 11.66", ... },
  "valuation_multiples": { "val_tev_ebitda_fy_1": "36.61x", ... },
  "growth_yoy": { "grw_total_revenue_fy_1": "43.98%", ... },
  "ownership": { "own_holder_1_name": "BlackRock, Inc.", "own_holder_1_shares": 398213826, ... },
  "comparable_companies": { "comp_quick_comp_1": "AMD", ... },
  ...
}

FAQ

How many tokens is one company profile? About 21K tokens of JSON for a full profile (2,119 fields). daily_prices and daily_volumes are about 3.5K of that; drop them if your agent only needs fundamentals.

Can my agent call this through MCP? Yes. Point any MCP client at https://mcp.apify.com/?actors=workhard3000/tearsheet-pro with your Apify token as a Bearer header (see Connect your agent above).

How fresh is the data? Cached data is valid for 30 days. Use forceRefresh: true to get the latest available data at any time.

What currencies are supported? Over 30 currencies including USD, EUR, GBP, JPY, CNY, KRW, TWD, INR, and local reporting currency.

Can I fetch multiple companies at once? Yes. Enter comma-separated tickers (e.g. AAPL, MSFT, GOOGL). Each company is charged as a separate result event. For tickers from different countries, use the full Exchange:Ticker format.

What happens if the cache is cold? A live refresh is triggered automatically. Results arrive within ~2 minutes. You are charged the fresh-result rate.

What if I enter a wrong ticker? Invalid tickers return an error message and are never charged. You pay $0 for bad input.

How does this compare to Financial Datasets API? Financial Datasets covers 27,000 US tickers with separate endpoints for each data type ($200/month). Tearsheet Pro covers 30,000+ companies across 126 countries and returns everything in a single call, with no monthly commitment.

Can I use this for non-US companies? Yes. Tearsheet Pro covers 126 countries. Select a country to browse available tickers, or enter the exchange-prefixed ticker directly (e.g. TSE:7203 for Toyota).

Can I use this with my LLM or trading agent? Yes. The output is structured JSON with consistent field names across all 30,000+ companies. It works directly with LangChain, LangGraph, CrewAI, AutoGen, TradingAgents, or any LLM framework that can consume JSON. Use the Apify REST API to call Tearsheet Pro from your agent code, or use the Apify Python/JS SDK for native integration.

Is there an API? Yes. Every Apify actor exposes a REST API. You can trigger runs, poll for results, and download datasets programmatically. See the API tab on this actor's page.