How I Built a Universal MCP ↔ A2A Bridge: Architecture, Protocol Mapping, and What I Learned
The article discusses the development of Nexarion, a runtime bridge that connects two incompatible AI protocols: Anthropic's MCP and Google's A2A. The author outlines the architecture and protocol mapping used to facilitate communication between these systems. Key features include dynamic tool synthesis and a plugin system for middleware hooks, which enhance the bridge's functionality.
- ▪The AI agent ecosystem is currently divided between two standards, MCP and A2A, which do not interoperate.
- ▪Nexarion acts as a translation runtime that allows MCP clients to communicate with A2A agents seamlessly.
- ▪The bridge includes a discovery layer, a translation layer, and a routing layer to manage interactions between the two protocols.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3935563) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Vahap Ogut Posted on May 16 How I Built a Universal MCP ↔ A2A Bridge: Architecture, Protocol Mapping, and What I Learned #ai #typescript #programming #opensource The AI agent ecosystem is fragmenting into two incompatible standards. On one side, Anthropic's MCP (Model Context Protocol) lets AI models use tools. On the other, Google's A2A (Agent-to-Agent) lets agents collaborate. They can't talk to each other.
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