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Build Java AI agents with real-time multi-protocol transport and MCP support.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "atmosphere" yet — see the docs or source repo.
I am building a Java AI agent. Using atmosphere, design an integration plan that supports WebSocket, SSE, and gRPC, and explain the core components, connection flow, and minimal code structure.
A multi-protocol integration plan with architecture notes, protocol layering, and a Java code skeleton.
I already have a Java agent built with @Agent. Explain how to expose it as an MCP-compatible real-time service with atmosphere, and add integration suggestions for A2A and AG-UI.
A step-by-step MCP publishing guide with compatibility advice, interface design points, and extension recommendations.
Using atmosphere, create a production deployment plan for a Java AI service covering WebTransport/HTTP3 support, connection reliability, observability, scaling, and recovery strategies.
A production deployment and operations plan covering protocol choices, monitoring metrics, and high-availability design.
Enable AI agents to communicate, route messages, and collaborate through MCP.
Connect AI agents to multiple APIs through one unified MCP gateway.
Enable cross-protocol discovery, messaging, and transactions for AI agents.
Connect LLMs with A2A agents for messaging, task management, and agent discovery.
Build a JWT-secured MCP server and AI agent for tool calling.
Monitor multi-agent workflows with live calls, sessions, and usage observability.