CopilotKit for Next.js Integration

Integrate CopilotKit AI components into your Next.js application to build intelligent, context-aware interfaces where AI agents can read application state and trigger actionable tools.

When to use

Use this skill when you need to:

• Build AI-powered chat interfaces in your Next.js app
• Create context-aware AI agents that understand current UI state
• Enable AI to trigger actions and mutate app state
• Integrate custom or self-hosted LLM endpoints
• Implement human-in-the-loop AI workflows
• Add AI copilots to SaaS dashboards or productivity tools
• Support multiple LLM providers with custom adapters
• Build agentic UIs with sidebar, popup, or headless chat

Core concepts

Mental Model

CopilotKit is a bridge between your Next.js frontend and an LLM runtime endpoint:

[Next.js Frontend] 
    ↕ state/actions/messages
[Copilot Runtime Endpoint]
    ↕ provider protocol
[LLM Adapter] → [OpenAI/Claude/Groq/Custom LLM]

The runtime:

• Manages conversation history
• Calls your LLM provider through an adapter
• Executes tools/actions triggered by the model
• Syncs generated content back to your UI

Key Primitives

• Copilot Runtime: Self-hosted endpoint managing message history, tool calls, and provider integration
• Readable State: App data exposed to the model via useCopilotReadable hooks for context
• Actions/Tools: Executable functions the model can trigger via useCopilotAction
• UI Components: CopilotPopup, CopilotSidebar, or custom headless chat
• Adapters: Provider integration layer (OpenAI, Groq, Google, custom self-hosted, etc.)
• Generative UI: Structured responses for interactive UI updates

Quick start

Basic Setup

npm install @copilotkit/react @copilotkit/sdk

Minimal Example

import { CopilotPopup } from "@copilotkit/react-ui";
import { CopilotKit } from "@copilotkit/react-core";

export default function App() {
  return (
    <CopilotKit runtimeUrl="http://localhost:8080/copilot">
      <YourApp />
      <CopilotPopup />
    </CopilotKit>
  );
}

Share State with AI

import { useCopilotReadable } from "@copilotkit/react-core";

export function TaskList({ tasks }) {
  useCopilotReadable({
    description: "List of tasks for the user",
    value: tasks
  });

  return (
    <ul>
      {tasks.map(task => <li key={task.id}>{task.title}</li>)}
    </ul>
  );
}

Enable AI-Triggered Actions

import { useCopilotAction } from "@copilotkit/react-core";

export function TaskPanel({ tasks, setTasks }) {
  useCopilotAction({
    name: "complete_task",
    description: "Mark a task as complete",
    parameters: [
      {
        name: "task_id",
        description: "The ID of the task to complete",
        type: "string"
      }
    ],
    handler: (taskId) => {
      setTasks(tasks.map(t => 
        t.id === taskId ? { ...t, completed: true } : t
      ));
    }
  });

  return (
    <div>
      {tasks.map(task => (
        <TaskCard key={task.id} task={task} />
      ))}
    </div>
  );
}

Capabilities

Context-Aware AI

• Read App State: Expose UI state, data, and context to the AI model
• Conversation History: Maintain conversation context across messages
• Dynamic Context: Update what the model sees as app state changes
• Structured Responses: Return structured data for interactive UI updates

Tool & Action System

• Define Custom Tools: Any JavaScript function can become an AI-callable tool
• Parameter Validation: Define required and optional parameters with types
• Error Handling: Handle tool failures gracefully with retry logic
• State Mutations: Actions can update React state, trigger API calls, or run complex workflows
• Human-in-the-Loop: Get user confirmation before executing critical actions

Provider Flexibility

• OpenAI Integration: Out-of-the-box support for GPT-4, GPT-4o, etc.
• Alternative Providers: Support for Groq, Google, Anthropic, etc.
• Custom Adapters: Implement adapters for proprietary or self-hosted models
• Provider Agnostic: Switch providers without changing your UI code
• Self-Hosting: Deploy your own LLM runtime for privacy and cost control

UI Options

• Popup UI: Floating chat popup component
• Sidebar UI: Embedded sidebar copilot
• Headless: Build completely custom UI while using CopilotKit runtime
• Customizable Styling: Theme and style components to match your app
• Accessibility: Built-in keyboard navigation and screen reader support

Workflow

When implementing CopilotKit in your Next.js app:

1. Setup Runtime: Deploy or configure Copilot Runtime endpoint
2. Wrap App: Wrap your Next.js app with <CopilotKit> provider
3. Share State: Use useCopilotReadable to expose relevant app data
4. Define Actions: Use useCopilotAction to enable AI-triggered operations
5. Add UI: Include <CopilotPopup>, <CopilotSidebar>, or custom chat UI
6. Test & Refine: Iterate on state exposure and action definitions

Configuration Options

Runtime Configuration

<CopilotKit
  runtimeUrl="http://localhost:8080/copilot"  // Runtime endpoint
  credentials="include"                         // Include cookies
  headers={{                                    // Custom headers
    "Authorization": `Bearer ${token}`
  }}
>

Readable State Configuration

useCopilotReadable({
  description: "Clear description of this data",
  value: importantData,
  parentId: "parent-context",  // Nest within context
  categories: ["data", "state"] // Categorize for filtering
});

Action Configuration

useCopilotAction({
  name: "action_name",           // Unique identifier
  description: "What this does", // For AI model understanding
  parameters: [                   // Function parameters
    {
      name: "param_name",
      description: "Parameter description",
      type: "string",             // Type for validation
      required: true
    }
  ],
  handler: async (param) => {    // Async function to execute
    // Perform action, update state, call APIs
  }
});

Best Practices

State Sharing

• ✅ Expose only relevant state that the AI needs
• ✅ Use clear, descriptive names for readable state
• ✅ Update readables reactively as state changes
• ✅ Keep exposed state serializable
• ❌ Don't expose sensitive data (tokens, passwords)
• ❌ Don't expose extremely large objects

Actions

• ✅ Keep actions focused and single-purpose
• ✅ Include clear parameter descriptions
• ✅ Validate parameters before execution
• ✅ Handle errors gracefully with user feedback
• ✅ Use async/await for long-running operations
• ❌ Don't expose dangerous operations without confirmation
• ❌ Don't rely on implicit context

Security

• ✅ Validate all AI-triggered actions on the backend
• ✅ Implement proper authentication/authorization
• ✅ Log AI actions for auditing
• ✅ Use rate limiting on action endpoints
• ✅ Sanitize AI outputs before rendering
• ❌ Don't trust client-side validation alone
• ❌ Don't expose internal APIs directly

Provider Integration

OpenAI Adapter (Default)

import { CopilotKit } from "@copilotkit/react-core";

<CopilotKit 
  runtimeUrl="http://localhost:8080/copilot"
  credentials="include"
/>

Custom Provider Adapter

// Implement custom adapter for proprietary LLM
class CustomLLMAdapter extends CopilotKitAdapter {
  async chat(messages, model) {
    // Call your custom LLM endpoint
    const response = await fetch("https://your-llm/chat", {
      method: "POST",
      body: JSON.stringify({ messages, model })
    });
    return response.json();
  }
}

// Use in runtime
const adapter = new CustomLLMAdapter({ apiKey: process.env.CUSTOM_API_KEY });

Self-Hosted LLM

// Point to self-hosted Ollama, LM Studio, or vLLM
<CopilotKit
  runtimeUrl="http://localhost:8080/copilot"
  // Runtime configured to use self-hosted endpoint
/>

Real-World Patterns

Pattern 1: Task Automation in SaaS Dashboard

// Share CRM records and deal state
useCopilotReadable({
  description: "Current CRM records visible to user",
  value: crmRecords
});

// Enable bulk actions
useCopilotAction({
  name: "update_deal_status",
  description: "Update the status of one or more CRM deals",
  parameters: [/* ... */],
  handler: async (dealIds, newStatus) => {
    await updateDeals(dealIds, newStatus);
    refreshData();
  }
});

Pattern 2: Productivity App Assistant

// Expose task list and user preferences
useCopilotReadable({
  description: "User's tasks and productivity preferences",
  value: { tasks, preferences }
});

// Enable task manipulation
useCopilotAction({
  name: "suggest_task_reorganization",
  description: "Reorganize tasks based on priority",
  handler: async (strategy) => {
    const reorganized = reorganizeTasks(tasks, strategy);
    setTasks(reorganized);
  }
});

Pattern 3: E-Commerce Copilot

// Share cart state
useCopilotReadable({
  description: "Shopping cart contents and user profile",
  value: { cart, user }
});

// Enable checkout actions
useCopilotAction({
  name: "apply_promotion",
  description: "Apply a promotional code to the cart",
  handler: async (code) => {
    const discount = await validatePromo(code);
    updateCartDiscount(discount);
  }
});

Troubleshooting

Runtime Connection Issues

• ✓ Verify runtime endpoint is accessible
• ✓ Check CORS configuration
• ✓ Ensure credentials are correct
• ✓ Check browser console for connection errors

Actions Not Triggering

• ✓ Verify action names are unique
• ✓ Check parameter types match definitions
• ✓ Ensure handler function is provided
• ✓ Check for JavaScript errors in handler

State Not Updating

• ✓ Verify readables are wrapped with useCopilotReadable hook
• ✓ Ensure state is being updated in parent component
• ✓ Check that readables run on every render
• ✓ Verify state is serializable

Related Skills

• makefile-dev-workflow: Development workflow for the full stack
• playwright-ux-ui-capture: UI capture automation
• ux-ui-analyze-single-page: Single page UX analysis

Resources

• CopilotKit Official Documentation
• CopilotKit GitHub Repository
• Next.js Documentation
• React Hooks Documentation

Support

For issues or questions:

1. Check the CopilotKit documentation
2. Review the examples in the skill directory
3. Check runtime logs for errors
4. File an issue with reproduction steps