Financial Datasets MCP Server

Provides access to real-time and historical stock market data for AI assistants through the Model Context Protocol (MCP).

Local serverstdioPython 2.3k

What is the Financial Datasets MCP server?

Provides access to real-time and historical stock market data for AI assistants through the Model Context Protocol (MCP). Exposed over MCP by the financial datasets mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

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

Adding it to your client

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Its toolset

Everything the assistant can do here goes through one of these:

  • 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
  • Prerequisites — The Prerequisites tool exposed by this server
  • Installation — 1. Clone this repository: bash git clone https://github.com/financial-datasets/mcp-server cd mcp-server

Configuration

You will need one environment variable: FINANCIAL_DATASETS_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Python 3.10 or higher - uv package manager

Caveats

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 12 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Financial Datasets.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the financial datasets mcp server does with a few real requests.

When to reach for it

Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Financial Datasets's toolset — get_income_statements, get_balance_sheets, get_cash_flow_statements and 9 more — is a fair guide to whether it matches your workflow. It is maintained by financial-datasets; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Available tools

ToolWhat it does
get_income_statementsGet income statements for a company.
get_balance_sheetsGet balance sheets for a company.
get_cash_flow_statementsGet cash flow statements for a company.
get_current_stock_priceGet the current / latest price of a company.
get_historical_stock_pricesGets historical stock prices for a company.
get_company_newsGet news for a company.
get_available_crypto_tickersGets all available crypto tickers.
get_crypto_pricesGets historical prices for a crypto currency.
get_historical_crypto_pricesGets historical prices for a crypto currency.
get_current_crypto_priceGet the current / latest price of a crypto currency.
PrerequisitesThe Prerequisites tool exposed by this server.
Installation1. Clone this repository: bash git clone https://github.com/financial-datasets/mcp-server cd mcp-server

How to install the Financial Datasets MCP server

3. Add the following configuration:
   ```json
   {
     "mcpServers": {
       "financial-datasets": {
         "command": "/path/to/uv",
         "args": [
           "--directory",
           "/absolute/path/to/financial-datasets-mcp",
           "run",
           "server.py"
         ]
       }
     }
   }

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.10 or higher - uv package manager
VariableDescriptionRequired
FINANCIAL_DATASETS_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Financial Datasets to get income statements.
  • Use Financial Datasets to get balance sheets.
  • Use Financial Datasets to get cash flow statements.

Frequently asked questions

Financial Datasets provides an API for accessing real-time and historical stock market data, including income statements, balance sheets, cash flow statements, stock prices, and market news. It's designed for seamless integration with AI assistants through the Model Context Protocol (MCP).