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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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/vahapogut/how-i-built-a-universal-mcp-a2a-bridge-architecture-protocol-mapping-and-what-i-learned-df3 |
| Publication time | Sat, 16 May 2026 22:23:07 +0000 |
| Retrieval time | 2026-05-16T22:40:19.056Z |
| Last seen | 2026-05-16T22:40:19.056Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | sP_tKSTLMBNM |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).