Copilotkit
The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol
Last verified:
What is Copilotkit?
CopilotKit is an open‑source frontend stack that lets developers embed AI copilots, agents, and generative UIs directly into React (and soon Angular) applications. It provides the UI infrastructure and hooks to connect any agent backend—such as LangChain, LangGraph, Google ADK, or custom agents—to your app for chat panels, canvas interfaces, and in‑app actions. The platform is designed to handle shared state, real‑time context awareness, and tool calling so that agents can interact with your application’s UI and data in a way that feels native to the product.
CopilotKit focuses on what it calls the ‘agentic frontend’: components that render tools as UI elements, dynamic generative UI that updates as the agent runs, and bi‑directional state sync between the agent and the app. This makes it possible to build workflows where the copilot can adjust forms, tables, or dashboards on the fly, and can be triggered from buttons, textareas, or dedicated copilot panels. The stack also supports human‑in‑the‑loop checkpoints, so users can review and approve actions before the agent executes them, which is useful for high‑stake or regulated workflows.
The tool is aimed primarily at product teams and frontend engineers who want to ship production‑ready AI copilots inside their own apps without reinventing the UI plumbing. It suits both startups experimenting with agent‑native features and large enterprises that need observability, deployment flexibility, and enterprise‑grade controls. Because the core framework is open source and MIT‑licensed, it is also attractive to teams that want to self‑host or deeply customize the agent frontend while still being able to plug into CopilotKit’s runtime, analytics, and enterprise intelligence layers.
Copilotkit pricing
Pricing model: Freemium
CopilotKit offers a free Developer plan that includes one developer seat, VPC or on‑prem runtime‑only deployment, five‑day thread retention, 200 max threads, 1 GB of multimodal storage, and Discord community support. The Pro plan costs 39 USD per developer per month for up to five seats and increases thread retention to five days, max threads to 5,000, and multimodal storage to 10 GB while keeping on‑prem or VPC hosting. The Team plan costs 500 USD per month with five seats included and raises thread retention to 14 days, max threads to 25,000, and multimodal storage to 100 GB, plus dedicated Slack support. The Enterprise plan is custom‑priced from 5,000 USD per month onward with unlimited threads, custom thread retention, and full enterprise deployment options including on‑prem and VPC. In addition the core framework is open source and free to self‑host under the MIT license, with premium features available via the paid plans.
Copilotkit pros
- Open‑source core framework under MIT license
- Frontend SDKs for React and Angular with full TypeScript support
- Supports generative UI where agents render UI components dynamically
- Bidirectional agent‑app state sync with real‑time context
- Headless UI components for fully custom copilot designs
- In‑app actions that let agents execute app workflows and API calls
- Integrates with multiple agent backends including LangChain and LangGraph
- Support for multiple LLMs and custom LLM backends
- Built‑in support for protocols like AG‑UI, MCP, and A2A
- CopilotKit Inspector for real‑time agent debugging and inspection
- Thread persistence and history for multi‑session conversations
- Observability hooks for custom logging and monitoring
- Support for human‑in‑the‑loop workflows with approval checkpoints
- Enterprise Intel l igence platform for thread analytics and learning
- Self‑hosted or fully managed deployment options in CopilotKit Cloud
Copilotkit cons
- Primarily focused on React and Angular, limiting other frontend stacks
- Complexity of agent‑frontend patterns can steepen learning curve
- Enterprise Intelligence Platform features are gated behind paid tiers
- Cloud hosting and some advanced analytics are still in early access
- Some advanced features such as A/B testing and RL‑based self‑improvement are coming soon rather than fully stable
- Self‑hosting the full stack requires DevOps and infrastructure effort
- Customization of advanced UI and agent behaviors demands strong frontend engineering
- Documentation assumes some comfort with agent frameworks and APIs
- Higher‑end tiers can be expensive for small teams or startups
- Limited public documentation around edge‑case integrations and debugging scenarios
Frequently asked questions about Copilotkit
What is CopilotKit and who is it for?
CopilotKit is a frontend stack for AI agents and generative UI that lets you connect any agent backend to your React or Angular app for chat, canvas, and in‑app AI workflows. It is designed for product teams and frontend engineers who want to build production‑ready AI copilots inside their own applications without building the UI plumbing from scratch.
Is CopilotKit open source?
Yes, the core CopilotKit framework is open source under the MIT license and free to use and self‑host. Some advanced features, analytics, and enterprise deployment options are offered as premium capabilities through paid plans.
Which frameworks and backends can I connect?
CopilotKit supports a wide range of agent backends including LangChain, LangGraph, Google ADK, Mastra, MS Agent Framework, and custom frameworks via the AG‑UI protocol. It also connects to any LLM provider and supports protocols such as MCP and A2A for broader agent interoperability.
Can I use CopilotKit without React?
CopilotKit is primarily built for React with a first‑class React SDK, but there is also an official Angular client. If you are not using React or Angular, you would need to adapt the frontend stack yourself or build on top of the open‑source core components.
What is generative UI in CopilotKit?
Generative UI is a feature that lets AI agents dynamically render and update UI components such as forms, buttons, cards, and tables while the agent runs. This means the copilot can create interactive interfaces on the fly rather than just returning text, giving you richer, more integrated experiences inside your app.
How does agent‑app state sync work?
CopilotKit keeps the agent and the app in sync by propagating app state to the agent and reflecting agent state changes back into the UI. This bidirectional sync lets agents read current form values, table selections, or routing state, and the app can react immediately when the agent updates variables or starts new steps.
What is the CopilotKit Inspector?
The CopilotKit Inspector is a debugging and monitoring tool that lets you inspect all agent‑user interactions in real time and historically. You can see what prompts were sent, which tools were called, and how state changed over time, helping you debug behavior and performance issues.
Can I self‑host CopilotKit?
Yes, CopilotKit can be self‑hosted; the core framework is open source and can run on your own infrastructure. The Enterprise Intelligence Platform explicitly supports VPC and on‑prem deployments, giving you control over where data and agent runtime live.
What analytics and monitoring features are included?
CopilotKit provides thread history, observability hooks for programmatic access to events, and analytics dashboards in the Enterprise Intelligence Platform. These features let you track usage, detect regressions, and structure data for A/B testing and continuous learning over time.
How does the Enterprise Intelligence Platform help agents improve?
The Enterprise Intelligence Platform adds thread persistence, analytics, and continuous learning layers so agents can learn patterns from user interactions and adjust behavior over time. It includes data lakehouse‑style analytics and coming‑soon reinforcement‑learning‑based self‑improvement to make agents more effective without manual retraining.