🎬 AI-Powered Stock Price Movement Prediction: Playwright + Python + Claude Desktop LLM + MCP Server Demo

🚀 Watch an end-to-end AI-powered stock price movement prediction system in action!

In this demo, I showcase a complete pipeline that predicts stock price movements using modern AI and automation tools. The system analyzes Reliance Industries Ltd (RIL) stock data scraped from BSEIndia.com and delivers human-readable predictions. 

🔧 𝗧𝗢𝗢𝗟𝗦 & 𝗧𝗘𝗖𝗛𝗡𝗢𝗟𝗢𝗚𝗜𝗘𝗦 𝗨𝗦𝗘𝗗:

✅ Playwright Python — Web automation for scraping live stock data
✅ Machine Learning — Predictive model for forecasting close price
✅ Claude Desktop LLM — AI-powered analysis and summarization
✅ Local MCP Server — Custom MCP server connecting all components

📊 𝗪𝗛𝗔𝗧 𝗧𝗛𝗜𝗦 𝗗𝗘𝗠𝗢 𝗖𝗢𝗩𝗘𝗥𝗦:

🔷 Real-time data scraping from BSEIndia.com
🔷 Automated capture of market depth & financials
🔷 Generation of analytical visualizations:
         ⭐ Open/High/Low/Close Price Comparison Chart
         ⭐ Trading Volume & Spread Analysis
         ⭐ Future Close Price Predictions Table
🔷 AI-powered summarization into actionable insights

🛠️ 𝗠𝗖𝗣 𝗦𝗘𝗥𝗩𝗘𝗥 𝗔𝗥𝗖𝗛𝗜𝗧𝗘𝗖𝗧𝗨𝗥𝗘:

⚡ Tool 1: run_playwright_test — Executes Playwright script
⚡ Tool 2: summarize_outputs — Processes graphs for Claude LLM

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🎬 SAP S/4HANA Finance Demo AR, AP & Financial Statements Automation with Tricentis Tosca

🔷 Overview

🔵 Demonstrating SAP S/4HANA’s Accounts Receivable, Accounts Payable, and Balance Sheet / Income Statement Overview dashboards
🔵 Automating financial processes using Tricentis Tosca
🔵 Executing three test cases: Receivables, Payables, and Financial Statements
🔵 Powered by Tosca’s model-based test automation for seamless validation
🔵 End‑to‑end test execution performed directly through Tosca

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 Using MCP Server &Tools, executed Bank Deposit & Funds Transfer, with GitHub Copilot & Claude AI LLM

  ✅ MCP Server setup: Created a MCP server with three tools (deposit, withdraw, fund-transfer) that call the bank app APIs. 

✅ Code-base & Integration: Bank Application in Java + JavaScript, integrated with GitHub Copilot and Claude Desktop for orchestration. 

✅ Validation Layers: Every tool triggers API, database, and Selenium UI (POM) validations. 

🔵 ✔️ Example — Deposit: "Deposit 1000 → account A98D5": API, DB, and UI tests run; summary logged. 

🔵 ✔️ Example — Fund transfer: "Transfer 1000 → I6728C→ A98D5": API, DB (source & target), and UI tests run for both accounts; summary logged. 

🔵 ✔️ Claude Desktop runs the same flow — API, DB, UI validations, transaction history and overall test results reported. 

✅ Outcome: End-To-End demo showing LLM-driven orchestration of MCP Server & Tools + Multi-layer verification (API → DB → Selenium UI) with clear pass/fail summaries.

 

 

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