Claude Code can now connect to financial datasets in seconds. Prompt for financial research, company data, access to 17,000+ stocks, and much more. Here’s how to connect in just 60 seconds: 1. Open Claude Code and paste: “claude mcp add –transport http financial-datasets https:// mcp. financialdatasets. ai/” 2. Authenticate Type: “/mcp” inside Claude Code and complete the OAuth flow in your browser. You can verify the server is connected at any time: “claude mcp list” 2. Start prompting Example prompts: “What is Apple’s current P/E ratio and market cap?” “Show me Tesla’s income statement for the last 4 quarters.” “How has Bitcoin’s price changed over the past year?” 3. Help If you run into errors, just ask Claude to help you by scanning the official docs here: https://docs.financialdatasets.ai/mcp-server#claude-code…

MCP Server - Financial Datasets

Source: https://docs.financialdatasets.ai/mcp-server

Documentation Index Fetch the complete documentation index at:https://docs.financialdatasets.ai/llms.txt Use this file to discover all available pages before exploring further.

Overview

Your AI assistant can use our official MCP server to access real-time financial data — stock prices, financials, SEC filings, news, and more.

Authentication

The MCP server supports two authentication methods:

• OAuth 2.1— Used by interactive clients (Claude,Claude Code,Cursor, etc.). When you first connect, you’ll be redirected to sign in with your Financial Datasets account. No API key is needed.
• API Key— Used forprogrammaticaccess via thehttps://mcp\.financialdatasets\.ai/apiendpoint. Include your key in theX\-API\-KEYheader.

If you don’t have an account,sign up for freeto get started. You can generate an API key from youraccount dashboard.

Getting Started

Choose your client below and follow the steps to connect.

• Claude
• Claude Code
• Claude Managed Agents
• Python
• Cursor

These steps work for bothClaude.ai(web) and theClaude Desktopapp.

1. Go toSettings→Connectors
2. ClickAddand enter the server URL:https://mcp\.financialdatasets\.ai/
3. ClickAdd custom connectorand complete OAuth authentication
4. In any new chat, click**+and enableFinancial Datasets**under Connectors

Run the following command in your terminal:

claude mcp add --transport http financial-datasets https://mcp.financialdatasets.ai/

Then authenticate by typing/mcpinside Claude Code and completing the OAuth flow in your browser.You can verify the server is connected at any time:

For production agents built on Anthropic’s hosted Managed Agents platform, authenticate with your API key using astatic\_bearervault credential.

1. Generate an API key from youraccount dashboard.
2. Create astatic\_bearervault credential pointing at our/apiendpoint:

{
  "type": "static_bearer",
  "mcp_server_url": "https://mcp.financialdatasets.ai/api",
  "token": "your-api-key"
}

1. Reference the vault ID when creating a session. Anthropic injectsAuthorization: Bearer <your\-api\-key\>on every MCP call.

See Anthropic’svault credentials docsfor full SDK examples in Python, TypeScript, Go, and Java.

For scripts, notebooks, and custom MCP integrations, connect to the/apiendpoint with your API key.Install the MCP Python SDK:

Connect, then call a tool — here we fetch the latest price for Apple:

import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

API_KEY = "your-api-key"
SERVER_URL = "https://mcp.financialdatasets.ai/api"

async def main():
    # Open an authenticated connection to the MCP server
    async with streamablehttp_client(
        SERVER_URL,
        headers={"X-API-KEY": API_KEY},
    ) as streams:
        read_stream, write_stream, _ = streams

        # Start an MCP session
        async with ClientSession(read_stream, write_stream) as session:
            await session.initialize()

            # Call any tool from the MCP Tools list
            result = await session.call_tool(
                "get_stock_price",
                {"ticker": "AAPL"},
            )
            print(result.content)

asyncio.run(main())

Generate an API key from youraccount dashboard.

Add the following to your~/\.cursor/mcp\.jsonfile:

{
  "mcpServers": {
    "financial-datasets": {
      "url": "https://mcp.financialdatasets.ai/"
    }
  }
}

Save the file and restart Cursor. The agent automatically detects all available tools and calls the relevant one when you ask financial data questions in chat.

Once connected, your AI assistant will have access to the following tools:Analyst Estimates

• get\_analyst\_estimates: Get analyst consensus estimates for a company, including revenue and earnings forecasts for upcoming periods.

Company Information

• get\_company\_facts: Get company details including employee count, sector, industry, exchange, and more.

Earnings

• get\_earnings: Get earnings data from SEC filings. Both modes return a flat list ofEarningsRecordentries — same shape in either mode. Withticker, returns the most recent SEC filings (8-K / 10-Q / 10-K / 20-F) for that company. Withoutticker, returns the most recently filed earnings across all covered companies (the real-time feed). Each entry exposesreport\_period,source\_type,filing\_date,accession\_number, plusquarterlyand/orannualfinancial blocks.

Financial Metrics

• get\_financial\_metrics: Get historical financial metrics such as P/E ratio, enterprise value, and revenue per share.
• get\_financial\_metrics\_snapshot: Get a snapshot of the latest financial metrics, including market cap, P/E ratio, and dividend yield.

Financial Statements

• get\_income\_statement: Get historical income statement data (revenue, expenses, net income).
• get\_balance\_sheet: Get historical balance sheet data (assets, liabilities, equity).
• get\_cash\_flow\_statement: Get historical cash flow statement data (operating, investing, financing activities).

Insider Trades

• get\_insider\_trades: Get insider trading transactions for a company, including purchases, sales, and other transactions by officers, directors, and major shareholders.

Interest Rates

• get\_interest\_rates: Get the latest policy interest rates from major central banks (e.g., FED, ECB, BOE, BOJ). Returns a snapshot of each bank’s current rate — no parameters required.

Key Performance Indicators

• get\_kpi\_guidance: Get forward-looking KPI guidance items issued by management in earnings releases and filings. Filter by ticker, period, metric name, and date range.
• get\_kpi\_metrics: Get historical KPI taxonomy metrics extracted from SEC filings (e.g., subscriber counts, ARPU, units sold). Filter by ticker, period (quarterly/annual), metric name, and date range.
• get\_kpi\_non\_gaap: Get non-GAAP KPIs reported by companies (e.g., Adjusted EBITDA, Free Cash Flow as defined by the company). Filter by ticker, period, metric name, and date range.

News

• get\_news: Get recent news articles for a specific company or the broad market. Pass a ticker for company-specific news, or omit the ticker for general market news.

SEC Filings

• get\_filings: Get a list of historical SEC filings for a company (10-K, 10-Q, 8-K, and more).
• get\_filing\_items: Extract specific sections from 10-K, 10-Q, and 8-K filings (e.g., Risk Factors, MD&A).
• list\_filing\_item\_types: Get a list of all extractable items for 10-K, 10-Q, and 8-K filings.

Segmented Financials

• get\_segmented\_financials: Get segment breakdowns from all three financial statement types (income statement, balance sheet, cash flow) in a single call. Returns revenue, operating income, and depreciation by product/segment; assets, goodwill, and long-lived assets by segment; and capital expenditure by segment.

Stock Prices

• get\_stock\_prices: Get historical stock price data (open, high, low, close, volume) over a date range with configurable intervals.
• get\_stock\_price: Get the latest price snapshot for a stock, including current price and OHLCV data.

Stock Screener

• screen\_stocks: Screen and filter stocks by financial metrics, valuation ratios, and company attributes. Combine multiple conditions to find stocks matching your criteria (e.g., revenue > $1B, P/E < 20, sector = “Technology”).
• list\_stock\_screener\_filters: Get a list of all available filter fields and operators for the stock screener, grouped by category.

Example Usage

After connecting, try asking your AI assistant questions like:

• “What is Apple’s current P/E ratio and market cap?”
• “Show me Tesla’s income statement for the last 4 quarters”
• “How has Bitcoin’s price changed over the past year?”
• “Break down Amazon’s revenue by business segment”
• “Find the Risk Factors section from Microsoft’s latest 10-K”
• “Compare Google and Meta’s revenue growth over the past 3 years”
• “Screen for technology stocks with a P/E ratio under 20 and revenue over $1 billion”
• “What’s happening in the markets today?”
• “What companies just reported earnings?”
• “Show me the latest earnings for Netflix”
• “What are the current central bank interest rates?”