A legal-document agent stack uses Google ADK, MCP, and four parsers to cut hallucinations to zero
MaryamMiradi · x · 2026-07-27
The author built an end-to-end AI agent system for legal documents using Google ADK, MCP, and four parsers, and says it is designed for zero hallucination workflows.
5-step design
- Business understanding: define strict boundaries with LegalAgentState, fail-safe defaults, allowed document types, and automatic human escalation when confidence is low.
- Data understanding: map what the system can and cannot answer, and score sources by recency and consistency.
- Data preparation: run multiple parsers and benchmark them; Docling (IBM) came out best in the example.
- Flow engineering: wire three agents — a generator, an auditor, and a router — so failed citations trigger regeneration.
- MCP reusability: expose extraction, quality checks, and citation validation as reusable MCP tools/prompts so LangGraph, CrewAI, and Google ADK can share the same server.
The post is also framed as a pitch for a 7-in-1 production AI agent course.
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