Financial Datasets MCP Server
LocalAbout Financial Datasets MCP Server
Financial Datasets MCP Server is an MCP server that gives Claude and other AI assistants access to stock market data from the Financial Datasets API. It is aimed at users who want to query financial statements and prices through an MCP interface.
Key features
- 01Income statements, balance sheets and cash flow statements
- 02Current and historical stock prices
- 03Company news retrieval
- 04Crypto ticker lists and crypto price queries
Use cases
- 01Asking Claude for a company's recent income statements
- 02Checking the current price of a stock
- 03Retrieving historical prices for a ticker over a date range
MCP support
The project runs as an MCP server and exposes tools for financial statements, stock prices, news and crypto prices to MCP clients. It requires a FINANCIAL_DATASETS_API_KEY.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEFinancial 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
-
Clone this repository:
git clone https://github.com/financial-datasets/mcp-server cd mcp-server -
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 -
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 -
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 -
Run the server:
uv run server.py
Connecting to Claude Desktop
-
Install Claude Desktop if you haven't already
-
Create or edit the Claude Desktop configuration file:
# macOS mkdir -p ~/Library/Application\ Support/Claude/ nano ~/Library/Application\ Support/Claude/claude_desktop_config.json -
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/uvwith the result ofwhich uvand/absolute/path/to/financial-datasets-mcpwith the absolute path to this project. -
Restart Claude Desktop
-
You should now see the financial tools available in Claude Desktop's tools menu (hammer icon)
-
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"
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.