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We now support 30+ agent harness integrations within OpenKnowledge. This is enabled by the Agent Client Protocol (ACP), which let us build our custom UI experience while fully leveraging the agents on your computer. Also powers our new Follow Mode and Comments features. Follow mode automatically navigates the IDE... show more

OpenKnowledge

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21,752 次观看 • 2 个月前 •via X (Twitter)

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Following Shopify's support for mcp-ui ( Postman has also added support to both our agent mode and MCP client. This is a huge step towards making agents more powerful and interactive and I am excited about the potential of generative UIs!

Following Shopify's support for mcp-ui ( Postman has also added support to both our agent mode and MCP client. This is a huge step towards making agents more powerful and interactive and I am excited about the potential of generative UIs!

Abhinav Asthana

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LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

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