A free MCP server to analyze and extract insights from public filings, earnings transcripts, financial metrics, stock market data, private market transactions, and deep web-based research within Claude Desktop and other popular MCP clients.

A set of tools for dealing with SEC EDGAR corporate filings

Exploring Causal Inferences in Finance with Graph Neural Networks

🏛️ Open-source toolkit for accessing SEC EDGAR financial data with Python and TypeScript/JavaScript SDKs. Features comprehensive parsing for 10-K, 10-Q, 8-K forms, XBRL financial data extraction, and real-time company filings retrieval.

Streams new SEC Filings in real-time using Phoenix LiveView

EDGAR Analytics – Python Library for Extracting, Analyzing, and Forecasting SEC EDGAR Filings. Streamline your financial analysis with comprehensive metrics, growth rates, and automated reporting capabilities.

AI agent toolkit for accessing and analyzing SEC EDGAR filing data. Build intelligent agents with LangChain, MCP-use, Gradio, Dify, and smolagents to analyze financial statements, insider trading, and company filings.

This project predicts corporate default probability using sentiment analysis of annual reports and financial data from U.S. companies. Key steps included data preprocessing, textual analysis, feature selection, and testing machine learning models. A Random Forest classifier was identified as the best model, trained, optimized, and exported for use.

Real-Time SEC 8-K Filing Analyzer for Financial Modeling

Stock market news API, developed by traders and investors for traders and investors.

Scrapes ticker info from various sites

A Python tool for extracting stock repurchase program data from SEC 10-Q and 10-K filings

📊 Hedge Fund Tracker: Track hedge fund portfolios and investment strategies using SEC filings

Track insider trades and political stock transactions in real-time. Monitor SEC filings, analyze patterns, and get AI-powered insights on market-moving trades.

Tournament game for terminal in C++ (final project for university CS1 course)

🍺 Homebrew tap for piquette/edgr

AI-powered SEC filing analysis using RAG. Reduces 4-hour document analysis to 3 seconds with 90%+ accuracy. Built with Python, FastAPI, PostgreSQL, and Gemini AI.

LLM-powered financial document analysis using RAG

Financial analysis automation tool that transforms SEC 10-K filing data into actionable investment insights. Interactive chatbot provides revenue analysis, growth trends, risk assessments, and portfolio recommendations for Microsoft, Apple, and Tesla through natural language queries.