What data sources does the server use?
All stock data is fetched live from Yahoo Finance via yfinance. News headlines and URLs are scraped from Finviz for the `get_stock_news` tool.
@edenmargolis
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"Advanced-Stock-Market-Analysis-MCP-Server": {
"command": "uv",
"args": [
"pip",
"install",
"-r",
"requirements.txt"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A powerful, extensible server built using the Model Context Protocol (MCP) and yfinance for advanced stock market analysis. It provides a suite of tools for retrieving, analyzing, comparing stock data, and performing sector and market sentiment analysis. Designed for developers and analysts who need live financial data and technical indicators via an MCP-compatible client.
Clone the repository, install dependencies with uv pip install -r requirements.txt, then start the server with uv run mcp install main.py. Interact using any MCP-compatible client (e.g., Claude, Cursor) by making tool calls such as { "ticker": "AAPL" } to get stock info.
All stock data is fetched live from Yahoo Finance via yfinance. News headlines and URLs are scraped from Finviz for the `get_stock_news` tool.
The server requires Python 3.8+ and relies on yfinance, fastapi, requests, and beautifulsoup4. Dependencies are listed in `requirements.txt`.
Built-in error handling and retry logic ensure robust operation when fetching data or scraping news.
The server runs as a standard MCP tool server—no authentication details are provided in the README. It is designed to be used with any MCP-compatible client.
The README suggests using the prompt: “Get the latest news of {{ticker}} stock. For each article, read the full content, assess whether the sentiment is positive, negative, or neutral, and then write a summary of the overall sentiment and your conclusions.”

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