How do I install Cabrini Market Data?

Copy the http config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Cabrini Market Data need an API key?

No required environment variable is listed on this record.

What transport does Cabrini Market Data use?

Cabrini Market Data is reached over HTTP.

When was Cabrini Market Data last checked?

Last checked 2026-10-16. US equity data for AI agents — 23 years intraday + daily, SEC filings. x402 USDC payments.

Cabrini Market Data MCP server

cabrini

US stock market data for AI agents. 23 years of intraday and daily bars, SEC fundamentals, filings, and insider data — every US equity from 2003 to present.

Pay per query with USDC on Base (x402). No API keys, no subscriptions, no signup.

Install

pip install cabrini

Quick start

from cabrini import Cabrini

c = Cabrini(private_key="0x...")  # any Base wallet with USDC

# Intraday bars (pct from daily open) — $0.025
bars = c.query("AAPL", "2024-01-15")

# Daily OHLCV + VWAP (absolute prices) — $0.001/year
daily = c.daily("TSLA", "2024-01-01", "2024-03-31")

# SEC fundamentals — $0.02
fins = c.fundamentals("NVDA")

# Full research brief — $0.25
brief = c.brief("MSFT")

LangChain

from cabrini import get_langchain_tools
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

tools = get_langchain_tools(private_key="0x...")
agent = create_react_agent(ChatOpenAI(model="gpt-4o"), tools)

result = agent.invoke({"messages": [
    {"role": "user", "content": "What was NVDA's trading volume on the day of their last earnings?"}
]})

CrewAI

from cabrini import get_crewai_tools
from crewai import Agent, Task, Crew

tools = get_crewai_tools(private_key="0x...")

analyst = Agent(
    role="Financial Analyst",
    goal="Analyze stock performance using real market data",
    tools=tools,
)

task = Task(
    description="Compare AAPL and MSFT intraday volatility on 2024-06-15",
    agent=analyst,
)

Crew(agents=[analyst], tasks=[task]).kickoff()

MCP (Claude, Cursor, etc.)

Point any MCP client at https://cabrini.ai/mcp:

{
  "mcpServers": {
    "cabrini": {
      "url": "https://cabrini.ai/mcp"
    }
  }
}

All endpoints

Method	Price	Description
`query(ticker, date)`	$0.025	Full trading day of intraday bars
`daily(ticker, start, end)`	$0.001/year	Daily OHLCV + VWAP — the absolute prices
`batch(tickers, date)`	$0.02/ticker	Several tickers, one date, no limit
`range(ticker, start, end)`	$0.01/trading day	Multi-day intraday, no limit
`bars(ticker, date, interval)`	$0.015/day	Resampled intraday, 3-240 min
`scan(date, **criteria)`	$0.10	Screen every US stock; needs >= 1 criterion
`tickers(date)`	$0.005	List traded tickers
`company(ticker)`	$0.005	Company profile from SEC EDGAR
`fundamentals(ticker)`	$0.02	SEC quarterly data
`filings(ticker)`	$0.01 / $0.05	SEC filing index; +extracted section text
`insiders(ticker)`	$0.02	Insider transactions (Form 4)
`brief(ticker)`	$0.25	Joined research brief

Prices are quoted live in each 402 response and the client pays whatever the server asks — this table is documentation, not the source of truth.

Output format

Intraday methods (query, range, batch, bars) return fractional change from the daily open, not price levels:

{"window_start": "2024-01-02T14:30:00", "timestamp": 1704204600000000000,
 "pct_open": 0.0, "pct_high": 0.0012, "pct_low": -0.0003, "pct_close": 0.0008,
 "volume": 47000, "transactions": 312}

pct_x = (bar_x - day_open) / day_open, so 0.0012 is +0.12%.

daily() carries the absolute levels — open, high, low, close, volume, transactions and VWAP. Combine the two to reconstruct prices:

day = c.daily("AAPL", "2024-01-02", "2024-01-02")["data"][0]
bars = c.query("AAPL", "2024-01-02")["data"]
close_price = day["open"] * (1 + bars[-1]["pct_close"])

Use daily() rather than a third-party open: our reference is the first bar of the session and includes pre-market, so an external 09:30 open will not reconcile exactly.

How payment works

Every paid request uses x402 — an open protocol for HTTP micropayments:

Client sends request → server returns 402 with a PAYMENT-REQUIRED header
Client signs a USDC transfer authorization (EIP-3009)
Client replays request with X-PAYMENT header containing the signed authorization
Cloudflare edge worker verifies signature, submits to Base, forwards to origin
Origin returns data

The Cabrini client handles all of this automatically. You just need a wallet with USDC on Base.

Get USDC on Base

Bridge from Ethereum: bridge.base.org
Buy directly: Coinbase → send USDC to your wallet on Base network
Faucet (testnet): not needed, mainnet USDC is cheap ($0.025/query)

cabrini

US stock market data for AI agents. 23 years of intraday and daily bars, SEC fundamentals, filings, and insider data — every US equity from 2003 to present.

Pay per query with USDC on Base (x402). No API keys, no subscriptions, no signup.

Install

pip install cabrini

Quick start

from cabrini import Cabrini

c = Cabrini(private_key="0x...")  # any Base wallet with USDC

# Intraday bars (pct from daily open) — $0.025
bars = c.query("AAPL", "2024-01-15")

# Daily OHLCV + VWAP (absolute prices) — $0.001/year
daily = c.daily("TSLA", "2024-01-01", "2024-03-31")

# SEC fundamentals — $0.02
fins = c.fundamentals("NVDA")

# Full research brief — $0.25
brief = c.brief("MSFT")

LangChain

from cabrini import get_langchain_tools
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

tools = get_langchain_tools(private_key="0x...")
agent = create_react_agent(ChatOpenAI(model="gpt-4o"), tools)

result = agent.invoke({"messages": [
    {"role": "user", "content": "What was NVDA's trading volume on the day of their last earnings?"}
]})

CrewAI

from cabrini import get_crewai_tools
from crewai import Agent, Task, Crew

tools = get_crewai_tools(private_key="0x...")

analyst = Agent(
    role="Financial Analyst",
    goal="Analyze stock performance using real market data",
    tools=tools,
)

task = Task(
    description="Compare AAPL and MSFT intraday volatility on 2024-06-15",
    agent=analyst,
)

Crew(agents=[analyst], tasks=[task]).kickoff()

MCP (Claude, Cursor, etc.)

Point any MCP client at https://cabrini.ai/mcp:

{
  "mcpServers": {
    "cabrini": {
      "url": "https://cabrini.ai/mcp"
    }
  }
}

All endpoints

Method	Price	Description
`query(ticker, date)`	$0.025	Full trading day of intraday bars
`daily(ticker, start, end)`	$0.001/year	Daily OHLCV + VWAP — the absolute prices
`batch(tickers, date)`	$0.02/ticker	Several tickers, one date, no limit
`range(ticker, start, end)`	$0.01/trading day	Multi-day intraday, no limit
`bars(ticker, date, interval)`	$0.015/day	Resampled intraday, 3-240 min
`scan(date, **criteria)`	$0.10	Screen every US stock; needs >= 1 criterion
`tickers(date)`	$0.005	List traded tickers
`company(ticker)`	$0.005	Company profile from SEC EDGAR
`fundamentals(ticker)`	$0.02	SEC quarterly data
`filings(ticker)`	$0.01 / $0.05	SEC filing index; +extracted section text
`insiders(ticker)`	$0.02	Insider transactions (Form 4)
`brief(ticker)`	$0.25	Joined research brief

Prices are quoted live in each 402 response and the client pays whatever the server asks — this table is documentation, not the source of truth.

Output format

Intraday methods (query, range, batch, bars) return fractional change from the daily open, not price levels:

{"window_start": "2024-01-02T14:30:00", "timestamp": 1704204600000000000,
 "pct_open": 0.0, "pct_high": 0.0012, "pct_low": -0.0003, "pct_close": 0.0008,
 "volume": 47000, "transactions": 312}

pct_x = (bar_x - day_open) / day_open, so 0.0012 is +0.12%.

daily() carries the absolute levels — open, high, low, close, volume, transactions and VWAP. Combine the two to reconstruct prices:

day = c.daily("AAPL", "2024-01-02", "2024-01-02")["data"][0]
bars = c.query("AAPL", "2024-01-02")["data"]
close_price = day["open"] * (1 + bars[-1]["pct_close"])

Use daily() rather than a third-party open: our reference is the first bar of the session and includes pre-market, so an external 09:30 open will not reconcile exactly.

How payment works

Every paid request uses x402 — an open protocol for HTTP micropayments:

Client sends request → server returns 402 with a PAYMENT-REQUIRED header
Client signs a USDC transfer authorization (EIP-3009)
Client replays request with X-PAYMENT header containing the signed authorization
Cloudflare edge worker verifies signature, submits to Base, forwards to origin
Origin returns data

The Cabrini client handles all of this automatically. You just need a wallet with USDC on Base.

Get USDC on Base

Bridge from Ethereum: bridge.base.org
Buy directly: Coinbase → send USDC to your wallet on Base network
Faucet (testnet): not needed, mainnet USDC is cheap ($0.025/query)

Cabrini Market Data

Add this server

Host a copy with our keys and logs.

Related MCP

Related skills

cabrini

Install

Quick start

LangChain

CrewAI

MCP (Claude, Cursor, etc.)

All endpoints

Output format

How payment works

Get USDC on Base

Links

Cabrini Market Data

Add this server

Host a copy with our keys and logs.

Related MCP

Related skills

cabrini

Install

Quick start

LangChain

CrewAI

MCP (Claude, Cursor, etc.)

All endpoints

Output format

How payment works

Get USDC on Base

Links