
Running MCP Over NATS: Why It's the Best of Both Worlds
Discover how combining MCP's context management with NATS messaging delivers unprecedented value for production AI systems.
Deep dives on multi-agent architectures, scaling strategies, and the future of AI collaboration
Showing 13 of 13 articles
Discover how combining MCP's context management with NATS messaging delivers unprecedented value for production AI systems.
While Google pushes A2A and Anthropic champions MCP, they're missing the fundamental problem: these architectures don't scale.
Learn how to build agent swarms that can grow from 10 to 10,000 agents without architectural changes.
How ArtCafe.ai provides seamless interoperability between different agent communication protocols.
Benchmarking results comparing NATS message bus architecture with traditional agent-to-agent communication.
Discover how message bus architecture solves the fundamental scaling problems in multi-agent AI systems.
See how different agent architectures compare visually and why message bus patterns provide superior scaling.
Explore how treating agents as specialized tools rather than monolithic systems enables unprecedented flexibility.
Practical solutions to the most common problems teams face when building multi-agent systems.
Best practices for building secure, isolated multi-tenant agent systems for enterprise deployments.
Learn how shared memory graphs enable agents to collaborate without tight coupling.
Deep dive into NATS messaging patterns and ontology design for scalable agent communication systems.
Announcing ArtCafe.ai - an AI-native pub/sub platform built on NATS for secure, scalable agent communication with zero-ops onboarding.