Retrieves a comprehensive report for a given ticker symbol, including company overview, news, key metrics, performance, dates, analyst recommendations, and upgrades/downgrades.
Provides a list of stock options with the highest open interest, with filtering capabilities.
Retrieves historical price data for a specific ticker over a selected time period.
Fetches financial statements (income, balance, or cash flow) formatted in millions USD.
Retrieves details about major institutional and mutual fund holders for a given ticker.
Retrieves a formatted table of earnings history for a specific ticker.
Fetches the recent insider trading activity for a given ticker.
Retrieves the current CNN Fear & Greed Index score, rating, and classification.
Fetches historical CNN Fear & Greed Index data for a specified number of days.
Analyzes the trend of the CNN Fear & Greed Index over a specified number of days.
Calculates a specified technical indicator (SMA, EMA, RSI, MACD, BBANDS) for a ticker using daily closing prices over a given historical period. Requires optional TA-Lib installation.
Investor Agent is a comprehensive financial analysis tool that provides real-time market data, fundamental analysis, and technical indicators to Large Language Models. It leverages yfinance for market data retrieval and offers detailed ticker reports, options data, financial statements, institutional ownership information, and technical analysis capabilities. The server enables LLMs to access critical investment information including company overviews, earnings history, insider trading activity, and the CNN Fear & Greed Index. With optional technical analysis features, it can calculate indicators like SMA, EMA, RSI, MACD, and Bollinger Bands to support investment decision-making.
Investor Agent is a Model Context Protocol (MCP) server that equips Large Language Models with powerful financial analysis capabilities. It provides access to real-time market data, fundamental analysis, and technical indicators to help users make informed investment decisions.
For technical analysis features, you'll need the TA-Lib C library installed on your system. Follow the official installation instructions for your operating system before installing the TA-Lib Python wrapper.
The easiest way to run Investor Agent is using uvx, which fetches and runs the package without installing it:
# Run with core features only
uvx investor-agent
# Run with technical indicator features (requires TA-Lib C library)
uvx "investor-agent[ta]"
You can also install the package using uv:
# Install core features only
uv pip install investor-agent
# Install with technical analysis support
uv pip install "investor-agent[ta]"
Then run the server:
investor-agent
Once the server is running, you can use it with any MCP-compatible LLM client. The server provides a variety of tools for financial analysis, from basic ticker information to detailed technical indicators.
For optimal results:
The server automatically caches yfinance API responses for an hour in a local yfinance.cache file to improve performance and reduce redundant API calls.
For a complete investment workflow, consider combining Investor Agent with: