August 2026 Summaries

CopilotKit announced full AG-UI compatibility for Mastra agents through the enhanced `@ag-ui/mastra` integration, allowing a single agent to support features including generative UI, shared streaming state, human-in-the-loop interruptions, activity cards, frontend tools, memory, subagents, multimodal input, and persistent threads across web, mobile, Slack, Teams, and other Channels SDK platforms. Developers can begin with a CopilotKit CLI project or connect Mastra agents to the Copilot Runtime, then add CopilotKit chat components to their application. The update also improves support for Google’s framework-independent A2UI standard by enabling client-side catalog registration, dedicated sub-agent UI generation, validation-based self-healing output, in-place UI updates, and graceful fallback behavior. CopilotKit provides installation instructions, documentation, GitHub resources, and live demonstrations through its Dojo environments, while related posts highlight AG-UI support for React Native and CrewAI, along with deterministic AI-service testing through aimock.

CopilotKit has introduced a React Native client that allows AG-UI agents already used on the web to run natively in iOS and Android apps, with on-device frontend tools and interfaces rendered through React Native components rather than webviews. The setup requires React Native 0.70 or later, Node.js 20 or later, a model provider key, required Hermes polyfills imported in a specific order, and a self-hosted Copilot runtime that keeps prompts and model credentials on the developer’s server. Developers can choose headless, standard, or prebuilt-component package entry points, with the headless option recommended for custom interfaces because it avoids unnecessary native dependencies. The platform supports generative UI through device-side tools such as useRenderTool, state-driven integrations through useFrontendTool, and hooks for approvals, interruptions, suggestions, threads, and agent context. The post also notes networking considerations for physical devices, identifies native voice support as currently bring-your-own, and highlights A2UI, Google’s declarative, streaming-oriented generative UI specification, as a future direction for cross-platform agent interfaces.

CopilotKit announced ag-ui-crewai 0.3.0, an AG-UI protocol integration that exposes CrewAI Flows through streaming FastAPI endpoints so compatible clients can display structured reasoning, tool calls, state updates, multimodal input, human approvals, multi-agent activity, persistent threads, and generative UI without custom transport code. The release brings regular and Conversational Flows to feature parity, adds interrupt-and-resume workflows, checkpointing, agent attribution, backend tool-result rendering, and A2UI support, while fixing lost crew output and cross-thread conversation-state leakage. It supports CrewAI versions 1.0 through under 2.0 with features enabled according to runtime capabilities, though newer capabilities such as StreamFrame-based tools, interrupts, multimodal input, checkpointing, and Conversational Flows require specific later releases. The post also identifies implementation caveats involving inherited conversational Flow methods, an interrupt-outcome setting needed for recent CopilotKit resume behavior, and incomplete native support for audio, video, and document inputs, and directs developers to installation, documentation, source code, and 38 live examples.

aimock is an open-source, MIT-licensed mock server from CopilotKit designed to make testing AI applications faster, offline, and deterministic by replacing live calls to LLMs and related services with JSON-based fixtures. Developers can redirect existing API endpoints to a local server without modifying their applications or SDKs, avoiding token costs, API-key requirements, provider outages, and inconsistent test results. The tool supports a broad range of providers and services, including major LLM platforms, MCP and A2A protocols, vector databases, multimedia models, search, reranking, and moderation APIs. Recent additions include record-and-replay of production API traffic, drift detection for changing provider response formats, chaos testing for failures and latency, and expanded agentic-protocol support. The post reports more than one million weekly installs and adoption by projects including OpenClaw, TanStack, Mastra, and AG-UI, while also highlighting CopilotKit’s related Channels SDK for deploying AG-UI agents across Slack, Teams, and other messaging platforms.

A CopilotKit webinar demonstrated how to build and deploy a production-ready Slack agent using Mastra and the open-source Channels SDK, covering backend deployment, runtime connectivity, and native Slack operation. The SDK supports agents built with frameworks such as LangGraph, CrewAI, Microsoft Agent Framework, and custom AG-UI implementations, while allowing developers to define Slack Block Kit interfaces with JSX. It keeps streamed responses and tool calls within their originating threads, enables human approval workflows directly in Slack, and includes production-oriented capabilities such as provider connectivity, retries, and durable channel state. The session also addressed authentication, edge cases, and scalability, and directs developers to documentation, GitHub resources, and community support to connect an agent to Slack or other channels.

CopilotKit announced that Anthropic’s Claude Managed Agents now support AG-UI, allowing developers to connect server-managed agent sessions to compatible frontends with generative UI, streaming responses, tool calls, and persistent state across web frameworks and messaging platforms. The integration reduces the need to build custom transport, synchronization, and interface infrastructure, making it possible to connect an existing AG-UI frontend through configuration or create a production-ready agent experience using open-source components. Available resources include a reference integration repository, a Personal Finance Assistant quickstart built with CopilotKit, and a template for deploying managed agents in Slack or Microsoft Teams through the Channels SDK. Related announcements highlight the Channels SDK’s cross-platform agent deployment capabilities, CopilotKit support for Angular, and an “auto-tune” approach for training specialized models from production traffic.

CopilotKit has introduced the Channels SDK, an open-source library designed to integrate AG-UI agents into platforms like Slack, Microsoft Teams, and other chat applications seamlessly. This library allows agents to maintain context and memory within threads, streamlining integration by managing platform-specific details such as credentials and delivery rules. Users can add new platforms effortlessly through a centralized dashboard while using a single codebase. The SDK supports generative UI components, enabling interactive chats with features like charts and buttons, while also incorporating tools for automating tasks such as issue tracking or code deployment. Managed by CopilotKit Intelligence, the SDK ensures reliable delivery and state persistence, making it easier for developers to deploy agents across multiple channels without having to manage underlying infrastructure complexities.