finance-tools-mcp 0.0.5

A Model Context Protocol server for a collection of financial tools, https://github.com/VoxLink-org/finance-tools-mcp, modified from [investor-agent](https://github.com/ferdousbhai/investor-agent)

finance-tools-mcp: A Financial Analysis MCP Server

https://github.com/VoxLink-org/finance-tools-mcp

Overview

The finance-tools-mcp , modified from investor-agent, is a Model Context Protocol (MCP) server that provides comprehensive financial insights and analysis to Large Language Models. It leverages real-time market data, news, and advanced analytics to help users obtain:

• Detailed ticker reports including company overview, news, key metrics, performance, dates, analyst recommendations, and upgrades/downgrades.
• Options data highlighting high open interest.
• Historical price trends for stocks.
• Essential financial statements (income, balance sheet, cash flow) formatted in millions USD.
• Up-to-date institutional ownership and mutual fund holdings.
• Current and historical CNN Fear & Greed Index data and trend analysis.
• Prompts related to core investment principles and portfolio construction strategies.
• Earnings history and insider trading activity.
• Breaking world news from CNBC.
• FRED series search results.
• Technical indicators using ta-lib-python.

The server integrates with yfinance for market data retrieval and fetches Fear & Greed data from CNN.

It also includes tools for calculating mathematical expressions and technical indicators using ta-lib-python.

And Macro economic indicators using fredapi.

And breaking world news from cnbc.com.

Make sure to also enable web search functionality if you would like to incoporate latest news in your analysis.

Prerequisites

• Python: 3.10 or higher
• Package Manager: uv

Installation

First, install uv if you haven't already:

curl -LsSf https://astral.sh/uv/install.sh | sh

Then, you can run the finance-tools-mcp MCP server using uvx:

uvx finance-tools-mcp

If you want to use your own FRED API key, you can set it as an environment variable:

FRED_API_KEY=YOUR_API_KEY uvx finance-tools-mcp

Tools

The finance-tools-mcp server comes with several tools to support financial analysis:

Ticker Information

1. get_ticker_data

   • Description: Retrieves a comprehensive report for a given ticker symbol, including company overview, news, key metrics, performance, dates, analyst recommendations, and upgrades/downgrades.
   • Input:
     • ticker (string): Stock ticker symbol (e.g., "AAPL").
   • Return: A formatted multi-section report.

2. get_available_options

   • Description: Provides a list of stock options with the highest open interest.
   • Inputs:
     • ticker_symbol (string): Stock ticker symbol.
     • num_options (int, optional): Number of options to return (default: 10).
     • start_date & end_date (string, optional): Date range in YYYY-MM-DD format.
     • strike_lower & strike_upper (float, optional): Desired strike price range.
     • option_type (string, optional): Option type ("C" for calls, "P" for puts).
   • Return: A formatted table of options data.

3. get_price_history

   • Description: Retrieves historical price data for a specific ticker.
   • Inputs:
     • ticker (string): Stock ticker symbol.
     • period (string): Time period (choose from "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max").
   • Return: A table showing price history.

Financial Data Tools

1. get_financial_statements

   • Description: Fetches financial statements (income, balance, or cash flow) formatted in millions USD.
   • Inputs:
     • ticker (string): Stock ticker symbol.
     • statement_type (string): "income", "balance", or "cash".
     • frequency (string): "quarterly" or "annual".
   • Return: A formatted financial statement.

2. get_institutional_holders

   • Description: Retrieves details about major institutional and mutual fund holders.
   • Input:
     • ticker (string): Stock ticker symbol.
   • Return: Two formatted tables listing institutional and mutual fund holders.

3. get_earnings_history

   • Description: Retrieves a formatted table of earnings history.
   • Input:
     • ticker (string): Stock ticker symbol.
   • Return: A table displaying historical earnings data.

4. get_insider_trades

   • Description: Fetches the recent insider trading activity for a given ticker.
   • Input:
     • ticker (string): Stock ticker symbol.
   • Return: A formatted table showing insider trades.

CNN Fear & Greed Index Tools

1. get_current_fng_tool

   • Description: Retrieves the current CNN Fear & Greed Index score, rating, and classification.
   • Inputs: None
   • Return: A string containing the current index details.

2. get_historical_fng_tool

   • Description: Fetches historical CNN Fear & Greed Index data for a specified number of days.
   • Inputs:
     • days (int): Number of days of historical data to retrieve.
   • Return: A string listing historical scores and classifications.

3. analyze_fng_trend

   • Description: Analyzes the trend of the CNN Fear & Greed Index over a specified number of days.
   • Inputs:
     • days (int): Number of days to include in the trend analysis.
   • Return: A summary string including the latest value, average, range, trend direction, and classification.

Utility Tools

1. calculate

   • Description: Calculate the result of a mathematical expression. Supports Python math syntax and NumPy.
   • Input:
     • expression (string): The mathematical expression to evaluate.
   • Return: A string containing a JSON object with the calculation result (e.g., {'result': 10}).

2. calc_ta

   • Description: Calculate technical indicators using ta-lib-python (TA-lib) and NumPy.
   • Input:
     • ta_lib_expression (string): The TA-Lib expression to evaluate.
   • Return: A string containing the result of the TA-Lib calculation.

3. get_current_time

   • Description: Get the current time in ISO 8601 format.
   • Inputs: None
   • Return: A string representing the current time in ISO 8601 format.

Macro Tools

1. get_fred_series

   • Description: Fetches a FRED series by its ID.
   • Input:
     • series_id (string): FRED series ID.
   • Return: A string containing the FRED series data.

2. search_fred_series

   • Description: Searches for the most popular FRED series by keyword.
   • Input:
     • query (string): Keyword to search for.
   • Return: A string containing the search results.

3. cnbc_news_feed

   • Description: Retrieves the latest breaking world news from CNBC and others.
   • Inputs: None
   • Return: A string containing CNBC news feed.

Informational Prompts

1. investment_principles

   • Description: Provides a set of core investment principles and guidelines.
   • Inputs: None
   • Return: A string outlining several investment principles.

2. portfolio_construction_prompt

   • Description: Outlines a portfolio construction strategy incorporating tail-hedging.
   • Inputs: None
   • Return: A detailed prompt guiding the construction of a hedged portfolio.

Usage with MCP Clients

To integrate finance-tools-mcp with an MCP client (for example, Claude Desktop), add the following configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "investor": {
        "command": "path/to/uvx/command/uvx",
        "args": ["finance-tools-mcp"],
    }
  }
}

Debugging

You can leverage the MCP inspector to debug the server:

npx @modelcontextprotocol/inspector uvx finance-tools-mcp

or

npx @modelcontextprotocol/inspector uv --directory  ./ run finance-tools-mcp

For log monitoring, check the following directories:

• macOS: ~/Library/Logs/Claude/mcp*.log
• Windows: %APPDATA%\Claude\logs\mcp*.log

Development

For local development and testing:

1. Use the MCP inspector as described in the Debugging section.
2. Test using Claude Desktop with this configuration:

{
  "mcpServers": {
    "investor": {
      "command": "path/to/uv/command/uv",
      "args": ["--directory", "path/to/finance-tools-mcp", "run", "finance-tools-mcp"],
    }
  }
}

License

This MCP server is licensed under the MIT License. See the LICENSE file for details.

Samples

• carvana_analysis.md
• palantir_analysis.md
• pdd_analysis_20250503.md