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Your AI stack just stopped being closed. 🔓 TanStack AI now speaks AG-UI client-to-server. - The same client hits any AG-UI server. - Any AG-UI client hits a TanStack server. Zero breaking changes. Migration guide in the tweet below 👇

TANSTACK

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79,086 次观看 • 1 个月前 •via X (Twitter)

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MCP tools have only ever returned text for the model to read. Now they return interactive UI. 🪄 TanStack AI's new MCP Apps support renders ui:// widgets right in the chat - static or fully interactive, with a client/server bridge.

MCP tools have only ever returned text for the model to read. Now they return interactive UI. 🪄 TanStack AI's new MCP Apps support renders ui:// widgets right in the chat - static or fully interactive, with a client/server bridge.

TANSTACK

131,028 次观看 • 17 天前

We just released a new version of TanStack AI! 🚀 In today's release we have added client/server context for tools and middleware. Plug it into your useChat/chat and have it available, fully typesafe out of the box. 🔥

We just released a new version of TanStack AI! 🚀 In today's release we have added client/server context for tools and middleware. Plug it into your useChat/chat and have it available, fully typesafe out of the box. 🔥

TANSTACK

33,646 次观看 • 1 个月前

Files SDK 2.0 just dropped. This is the full-stack release: one storage API from server to browser. → Gateway: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚊𝚙𝚒 → Client: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚛𝚎𝚊𝚌𝚝, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚟𝚞𝚎, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚜𝚟𝚎𝚕𝚝𝚎 → Server: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚗𝚎𝚡𝚝, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚑𝚘𝚗𝚘, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚊𝚜𝚝𝚛𝚘, etc. → shadcn UI registry

Files SDK 2.0 just dropped. This is the full-stack release: one storage API from server to browser. → Gateway: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚊𝚙𝚒 → Client: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚛𝚎𝚊𝚌𝚝, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚟𝚞𝚎, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚜𝚟𝚎𝚕𝚝𝚎 → Server: 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚗𝚎𝚡𝚝, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚑𝚘𝚗𝚘, 𝚏𝚒𝚕𝚎𝚜-𝚜𝚍𝚔/𝚊𝚜𝚝𝚛𝚘, etc. → shadcn UI registry

Hayden Bleasel

40,960 次观看 • 21 天前

AI agents can finally talk to your frontend! The new AG-UI protocol lets your agents stream messages, sync state, call tools, and receive user input, live in the UI. It fills a critical gap in the agent ecosystem: ▸ MCP – agents to tools ▸ A2A – agents to agents ▸ AG-UI – agents to users, via frontends Connects to LangChain, CrewAI, and LlamaIndex (and more). 100% open-source.

AI agents can finally talk to your frontend! The new AG-UI protocol lets your agents stream messages, sync state, call tools, and receive user input, live in the UI. It fills a critical gap in the agent ecosystem: ▸ MCP – agents to tools ▸ A2A – agents to agents ▸ AG-UI – agents to users, via frontends Connects to LangChain, CrewAI, and LlamaIndex (and more). 100% open-source.

Lior⚡

15,514 次观看 • 1 年前

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.

Pratham

33,920 次观看 • 5 个月前

🚀 AG2 v0.11.1 is live! 🖥️ AG-UI Message Streaming – Real-time agent responses in your AG-UI frontends with new event-based streaming architecture. 🌊 A2A Streaming – Full streaming support for Agent-to-Agent communication! LLM text streaming now flows through A2A for real-time responses from remote agents, both server and client-side. 📡 OpenAI – Get more out of OpenAI's latest Responses API with stateful conversations, built-in tools (web search, image gen, apply_patch), reasoning model support, and enhanced cost tracking. Docs: 🛠️🪲 Bug fixes and maintenance #AG2 #AI #MultiAgentSystems #AIAgents #OpenSource #AGUI

🚀 AG2 v0.11.1 is live! 🖥️ AG-UI Message Streaming – Real-time agent responses in your AG-UI frontends with new event-based streaming architecture. 🌊 A2A Streaming – Full streaming support for Agent-to-Agent communication! LLM text streaming now flows through A2A for real-time responses from remote agents, both server and client-side. 📡 OpenAI – Get more out of OpenAI's latest Responses API with stateful conversations, built-in tools (web search, image gen, apply_patch), reasoning model support, and enhanced cost tracking. Docs: 🛠️🪲 Bug fixes and maintenance #AG2 #AI #MultiAgentSystems #AIAgents #OpenSource #AGUI

AG2

17,513 次观看 • 4 个月前

If you’re playing on MonkeyTilt, the outcome might already be decided BEFORE you bet “The cryptography behind every bet has always been sound” We tested it It isn’t... we sent two different client seeds for the same nonce same result both times the server is ignoring the client seed entirely the player has ZERO influence on outcomes — what we did — opened the MonkeyTilt provably fair verifier with a revealed server seed entered nonce 1 → got 3.04x changed the client seed same server seed, same nonce → 3.04x changed it again → 3.04x the client seed has ZERO effect on the outcome — why this matters — in a provably fair system the outcome is derived from: -server seed -client seed -nonce the client seed exists so the player contributes randomness the server CAN’T predict if it’s ignored the server knows every outcome BEFORE you bet the hash commitment proves nothing because the server already controls all the inputs — not a frontend bug — we checked the network traffic the verifier sends a WebSocket request with: -client seed -server seed -nonce the server receives different client seeds and returns the same result anyway request 1 → client_seed “Clientseed123456789” → 3.04x request 2 → client_seed “NEWSEED12345” → 3.04x this is the server ignoring input not a display issue — live bet traffic — placing a Limbo bet returns: -random_multiplier -total_payout -round_closed that’s it no hash no seed reference no nonce no proof seeds are fetched from a separate endpoint game engine and seed system are DISCONNECTED — nonce verification — you can only verify nonces you’ve already played in a real system all outcomes are predetermined once the server seed is committed - they’re deterministic blocking future nonces suggests results don’t exist until you bet — summary — -client seed ignored by server -no cryptographic proof in bet responses -game engine and seed system DISCONNECTED -nonce verification restricted this isn’t provably fair it looks like provably fair UI on top of server side RNG MonkeyTilt should probably address this anyone can verify this themselves in 60 seconds - open the verifier, change the client seed, watch the result stay the same

If you’re playing on MonkeyTilt, the outcome might already be decided BEFORE you bet “The cryptography behind every bet has always been sound” We tested it It isn’t... we sent two different client seeds for the same nonce same result both times the server is ignoring the client seed entirely the player has ZERO influence on outcomes — what we did — opened the MonkeyTilt provably fair verifier with a revealed server seed entered nonce 1 → got 3.04x changed the client seed same server seed, same nonce → 3.04x changed it again → 3.04x the client seed has ZERO effect on the outcome — why this matters — in a provably fair system the outcome is derived from: -server seed -client seed -nonce the client seed exists so the player contributes randomness the server CAN’T predict if it’s ignored the server knows every outcome BEFORE you bet the hash commitment proves nothing because the server already controls all the inputs — not a frontend bug — we checked the network traffic the verifier sends a WebSocket request with: -client seed -server seed -nonce the server receives different client seeds and returns the same result anyway request 1 → client_seed “Clientseed123456789” → 3.04x request 2 → client_seed “NEWSEED12345” → 3.04x this is the server ignoring input not a display issue — live bet traffic — placing a Limbo bet returns: -random_multiplier -total_payout -round_closed that’s it no hash no seed reference no nonce no proof seeds are fetched from a separate endpoint game engine and seed system are DISCONNECTED — nonce verification — you can only verify nonces you’ve already played in a real system all outcomes are predetermined once the server seed is committed - they’re deterministic blocking future nonces suggests results don’t exist until you bet — summary — -client seed ignored by server -no cryptographic proof in bet responses -game engine and seed system DISCONNECTED -nonce verification restricted this isn’t provably fair it looks like provably fair UI on top of server side RNG MonkeyTilt should probably address this anyone can verify this themselves in 60 seconds - open the verifier, change the client seed, watch the result stay the same

CoinBets🔍

20,973 次观看 • 3 个月前

✨AG-UI has been taking off! The Agent-User Interaction Protocol, allows you to bring AI agents into Frontend Apps. Excited to announce BIG updates & adoption by LlamaIndex 🦙 ,Agno, Google ADK, AWS & more! + New Building Experience🧑‍💻 npx create-ag-ui-app How it works & more 👇

✨AG-UI has been taking off! The Agent-User Interaction Protocol, allows you to bring AI agents into Frontend Apps. Excited to announce BIG updates & adoption by LlamaIndex 🦙 ,Agno, Google ADK, AWS & more! + New Building Experience🧑‍💻 npx create-ag-ui-app How it works & more 👇

CopilotKit🪁

70,648 次观看 • 1 年前

Finally, MCP servers can now deliver UI-rich experiences! MCP servers in Claude/Cursor don't offer UI any experience yet, like charts. It's just text/JSON. mcp-ui lets you add interactive web components to its output that can be rendered by the MCP client. 100% open-source!

Finally, MCP servers can now deliver UI-rich experiences! MCP servers in Claude/Cursor don't offer UI any experience yet, like charts. It's just text/JSON. mcp-ui lets you add interactive web components to its output that can be rendered by the MCP client. 100% open-source!

Avi Chawla

123,784 次观看 • 10 个月前

Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

CopilotKit🪁

31,845 次观看 • 9 个月前

Stop leaving your Agent stateless. Give it Threads in one hook. Resumable conversations that capture everything: messages, generative UI, shared state, human-in-the-loop workflows. Built on AG-UI, so it works with any compatible agent framework. docs:

Stop leaving your Agent stateless. Give it Threads in one hook. Resumable conversations that capture everything: messages, generative UI, shared state, human-in-the-loop workflows. Built on AG-UI, so it works with any compatible agent framework. docs:

Atai Barkai

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Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:

Atai Barkai

23,776 次观看 • 26 天前

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

Santiago

39,944 次观看 • 1 年前

I built a client onboarding system with a working UI in 12 minutes using one prompt Lyzr AI No dev time No rebuilding workflows for every client First join: Here’s exactly what it does and why this changes how I deliver projects 👇 Architect by Lyzr

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Nawi

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.@kspeyanski, Principal Software Engineer at Progress, Progress Kendo UI, invites you to his talk "Polymorphic React Components for Both the Client and the Server" at React Summit US! Join us in New York & Online on November 19 & 22.

.@kspeyanski, Principal Software Engineer at Progress, Progress Kendo UI, invites you to his talk "Polymorphic React Components for Both the Client and the Server" at React Summit US! Join us in New York & Online on November 19 & 22.

React Summit 🔥The biggest React conference

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Vapi

43,181 次观看 • 1 年前

Kicking off Day 1 of the launch week with the Chakra UI MCP Server 🖲️ Now, you can connect the entire Chakra UI design system to your AI workflow. Works with: - VS Code (GitHub Copilot) - Cursor - Claude Code - Windsurf - Zed Check it out: #ChakraLaunchWeek

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Chakra

19,610 次观看 • 11 个月前

i just built a full ios app to track client work and payments. • clean ui. • working logic. • ready to ship. took 15 minutes. zero code. this is the reality with tools like Superapp AI. people are still stuck in 2018.

i just built a full ios app to track client work and payments. • clean ui. • working logic. • ready to ship. took 15 minutes. zero code. this is the reality with tools like Superapp AI. people are still stuck in 2018.

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