StockScreener

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StockScreener is a project that demonstrates how to build a local AI assistant for in-depth stock analysis. It leverages MCP (Model Context Protocol), Ollama (running the Qwen3 language model), LangChain, and BeautifulSoup to retrieve and analyze financial data from Screener.in. The tool provides company details, profit analysis, and shareholding pattern analysis, all while ensuring seamless integration with MCP tools for enhanced functionality.

Características Principales

• Retrieves company details such as price, market cap, and financial ratios.
• Extracts quarterly and yearly net profit data.
• Analyzes shareholding patterns by promoters, DIIs, FIIs, and the public.
• Integrates with MCP tools for enhanced functionality.
• Utilizes local LLMs for privacy and control.
• 0 GitHub stars

Casos de Uso

• Automated stock analysis and reporting.
• Building a local AI-powered financial assistant.
• Custom financial data extraction and analysis.