Confluent + Google Cloud: Real-Time Backbone for Agentic AI
This post introduces the MCP/A2A proxy, a new component that acts as an intermediary for AI agents to communicate with each other (A2A) and with external resources (MCP). The proxy translates disparate MCP and A2A interactions into standardized messages within Confluent Cloud, providing a unified registry, protocol transformation, and service exposure capabilities. It enables existing microservices, legacy applications, and Flink jobs to be consumable by AI agents. The post also emphasizes how Confluent's event-driven architecture and asynchronous communication patterns, leveraging Kafka topics, support decoupled agent workflows and reliable message delivery. It highlights Confluent's role in providing real-time data to LLMs and knowledge bases, and acting as a proxy for inter-agent communication and workflow orchestration.
More from the Real-time Enterprise RAG trail
- Building an Agentic SOC on a Stream
- Hemut: Building the Internet of Freight on Real-Time Data
- New in Confluent Intelligence and AI Tools: Making Agents Native to the Stream, Expanded Model Support, New Agent Skills, and Copilot
- Customer Intelligence Hub for Real-Time GTM Insights
- RAG and GenAI for Customer 360 Architecture