I Built the Missing Layer Between A2A and MCP — Here's How NEXUS Coordinates AI Agents

Google's A2A protocol lets agents discover each other. Anthropic's MCP lets LLMs use tools. But what happens between discovery and execution? Who handles trust, billing, retries, and multi-agent workflows? Nothing. That gap is why 50% of enterprise AI agents still operate in complete isolation. I built NEXUS to fill it. The Problem Nobody Is Solving Here's the current state of multi-agent AI: A2A defines Agent Cards and JSON-RPC messaging. Great. Now agents can technically talk to each other. MCP lets Claude, GPT, and Cursor connect to external tools. Also great. CrewAI, LangGraph, AutoGen each coordinate agents within their own frameworks . But none of them answer these questions: I found an agent via A2A. Should I trust it? What's its track record? The agent completed my task. How do I pay it? I need 3 agents to work in sequence. Who orchestrates the workflow? An agent went down mid-task. Who retries? Who notifies? Every team building multi-agent systems answers these questions with