Financial Datasets MCP Server

Financial Datasets MCP Server avatar

by financial-datasets

Official Integrations

An MCP server for interacting with the Financial Datasets stock market API.

What is Financial Datasets MCP Server

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: Retrieve income statements for a stock
  • get_balance_sheets: Retrieve balance sheets for stock
  • get_cash_flow_statements: Retrieve cash flow statements for a stock
  • get_current_price: Get the latest price information for a stock
  • get_prices: Get historical stock prices with customizable date ranges and intervals
  • get_news: Get the latest news for a stock

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"

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.