End to End Production Legal AI Agents (MCP, Google ADK, Docling)

Most developers build "happy path" agents. Watch me build a 5-step production-ready legal AI agent system using Google ADK, MCP standardization, and Docling and Gemini Pro 3 as LLM. Perfect for developers, AI engineers, MLOps engineers, and AI practitioners building real-world AI Agents. » ♕ 𝗙𝗿𝗲𝗲 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 + 𝟮𝗫 𝗙𝗿𝗲𝗲 𝗚𝘂𝗶𝗱𝗲𝘀: https://www.maryammiradi.com/free-ai-... » ♔ 𝟳-𝗶𝗻-𝟭 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 (𝟲𝟬% 𝗢𝗙𝗙): https://www.maryammiradi.com/ai-agent... I Build in This Video: Understands Business Constraints (PydanticAI) Maps Data Reliability (Uncertainty Profiling) Parses Complex Legal Docs (Benchmarking Docling vs. LlamaIndex vs. PyPDF) Engineers the Flow (Google ADK Router & Auditor Agents) Standardizes for Reusability (MCP Server) 👨‍💻 Tech Stack Used: Google Agent Development Kit (ADK) Google Antigravity Google Gemini Pro Docling (IBM) Model Context Protocol (MCP) PydanticAI Python Realted Videos: I Built a €5.1B Vision Multi AI Agent Supply Chain (Gemini 3 Pro Vision, DeepSeek v3.2, LangGraph) ➡️   • End to End Supply Chain AI Agents (Gemini ...   Build 9 AI Agent Projects. Stand Out as AI Engineer [+ Gemini 3 Pre-Agent Booster] ➡️   • Build 9 AI Agent Projects. Stand Out as AI...   💡 Key Concepts Covered: ✅ Fail-safe defaults that prevent naive agent behavior ✅ Input validation for regulatory compliance ✅ OCR confidence checking and document quality gates ✅ Human-in-the-loop escalation mechanisms ✅ Data surface mapping for uncertainty profiling ✅ Multi-agent routing with regeneration logic ✅ MCP server architecture for cross-project reuse ⏱️ Chapters & Timestamps: 00:00 - The problem with "Naive" Agent Building 00:30 - The "Happy Path" Setup (And why it fails) - LLM 02:40 - Step 1: Business Understanding (Pydantic State & Fail-Safes) 05:00 - Step 2: Data Understanding (Surface Mapping & Uncertainty) 07:50 - Step 3: Data Preparation (Benchmarking Docling vs. LlamaIndex) 10:29 - Step 4: Flow Engineering with Google ADK (Auditor & Router Agents) 13:17 - Running the Multi-Agent System 14:20 - Step 5: Reusability with MCP (Model Context Protocol) 15:15 - Building the MCP Server & Tools 16:30 - Combining Frameworks (LangGraph, CrewAI, Google ADK) #aiagents #modelcontextprotocol #googleantigravity #aiengineer #aiengineering #aiprojects #docling