Financial Datasets MCP Server

Financial Datasets MCP Server

What is Financial Datasets MCP Server about?

The server exposes a collection of MCP tools that let Claude and other AI models query financial statements, real‑time and historical stock prices, company news, as well as crypto tickers and pricing data.

How to use Financial Datasets MCP Server?

1. Install prerequisites – Python 3.10+, uv package manager.
2. Clone the repo and set up a virtual environment with uv venv.
3. Add dependencies – uv add "mcp[cli]" httpx.
4. Provide API credentials – copy .env.example to .env and set FINANCIAL_DATASETS_API_KEY.
5. Run the server – uv run server.py.
6. Connect through Claude Desktop by adding an entry to claude_desktop_config.json that points to the uv executable and the project directory.

Key features of Financial Datasets MCP Server

• Retrieve income statements, balance sheets, and cash‑flow statements for any public company.
• Fetch current stock prices and historical price ranges.
• Access latest market news for a given ticker.
• List all available cryptocurrency tickers.
• Get current and historical crypto prices.
• Fully compatible with MCP‑enabled AI assistants (Claude Desktop, etc.).

Use cases of Financial Datasets MCP Server

• Financial analysis bots – generate earnings summaries, ratio calculations, or trend analyses on demand.
• Investment advisory assistants – provide up‑to‑date price quotes, chart data, and news headlines.
• Crypto monitoring tools – track price movements and historical performance for multiple tokens.
• Educational platforms – let students query real‑world financial statements for coursework.

FAQ from the Financial Datasets MCP Server

Q: Which programming languages are supported? A: The server itself runs on Python, but any MCP‑compatible client (Claude, custom AI pipelines, etc.) can call its tools.

Q: Do I need a paid API key? A: Yes, a valid FINANCIAL_DATASETS_API_KEY is required; obtain it from the Financial Datasets website.

Q: Can I run the server on Windows? A: Absolutely – the instructions work on Windows using PowerShell for the uv installation and activation (.venv\Scripts\activate).

Q: How do I add new tools? A: Extend server.py by defining additional MCP functions following the existing pattern and expose them in the tool list.

Q: Is rate limiting enforced? A: The underlying Financial Datasets API enforces its own limits; handle HTTP 429 responses in client code if needed.

Financial Datasets MCP Server

Introduction

This is a Model Context Protocol (MCP) server that provides access to stock market data from Financial Datasets.

It allows Claude and other AI assistants to retrieve income statements, balance sheets, cash flow statements, stock prices, and market news directly through the MCP interface.

Available Tools

This MCP server provides the following tools:

• get_income_statements: Get income statements for a company.
• get_balance_sheets: Get balance sheets for a company.
• get_cash_flow_statements: Get cash flow statements for a company.
• get_current_stock_price: Get the current / latest price of a company.
• get_historical_stock_prices: Gets historical stock prices for a company.
• get_company_news: Get news for a company.
• get_available_crypto_tickers: Gets all available crypto tickers.
• get_crypto_prices: Gets historical prices for a crypto currency.
• get_historical_crypto_prices: Gets historical prices for a crypto currency.
• get_current_crypto_price: Get the current / latest price of a crypto currency.

Setup

Prerequisites

• Python 3.10 or higher
• uv package manager

Installation

1. Clone this repository:

   git clone https://github.com/financial-datasets/mcp-server
   cd mcp-server
   

2. If you don't have uv installed, install it:

   # macOS/Linux
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Windows
   curl -LsSf https://astral.sh/uv/install.ps1 | powershell
   

3. Install dependencies:

   # Create virtual env and activate it
   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   
   # Install dependencies
   uv add "mcp[cli]" httpx  # On Windows: uv add mcp[cli] httpx
   
   

4. Set up environment variables:

   # Create .env file for your API keys
   cp .env.example .env
   
   # Set API key in .env
   FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key
   

5. Run the server:

   uv run server.py
   

Connecting to Claude Desktop

1. Install Claude Desktop if you haven't already

2. Create or edit the Claude Desktop configuration file:

   # macOS
   mkdir -p ~/Library/Application\ Support/Claude/
   nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
   

3. Add the following configuration:

   {
     "mcpServers": {
       "financial-datasets": {
         "command": "/path/to/uv",
         "args": [
           "--directory",
           "/absolute/path/to/financial-datasets-mcp",
           "run",
           "server.py"
         ]
       }
     }
   }
   

   Replace /path/to/uv with the result of which uv and /absolute/path/to/financial-datasets-mcp with the absolute path to this project.

4. Restart Claude Desktop

5. You should now see the financial tools available in Claude Desktop's tools menu (hammer icon)

6. Try asking Claude questions like:

   • "What are Apple's recent income statements?"
   • "Show me the current price of Tesla stock"
   • "Get historical prices for MSFT from 2024-01-01 to 2024-12-31"