Cabrini Py 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

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:

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

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

Get USDC on Base

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

Links

• Homepage: https://cabrini.ai
• API docs: https://cabrini.ai/docs
• Agent guide: https://cabrini.ai/agents
• MCP endpoint: https://cabrini.ai/mcp