CopilotKit Setup

Prerequisites

Live Documentation (MCP)

This plugin includes an MCP server (copilotkit-docs) that provides search-docs and search-code tools for querying live CopilotKit documentation and source code.

• Claude Code: Auto-configured by the plugin's .mcp.json -- no setup needed.
• Codex: Requires manual configuration. See the copilotkit-debug skill for setup instructions.

Environment

Before starting setup, verify:

1. Node.js >= 18 (required for fetch globals used by the runtime)
2. An AI provider API key (one of: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY)
3. A React-based frontend (Next.js App Router, Next.js Pages Router, Vite + React, or Angular)
4. A backend capable of running the runtime (same Next.js app via API routes, or a standalone Express/Hono server)

Framework Detection

Before generating any code, detect the project's framework by checking files in the project root. See references/framework-detection.md for the full decision tree.

Quick summary:

Setup Workflow

Step 1: Install packages

All packages use the @copilotkit namespace. The v2 API lives as subpath exports on the published packages.

Frontend + backend in the same Next.js app:

npm install @copilotkit/react-core @copilotkit/runtime hono

Frontend only:

npm install @copilotkit/react-core

Backend runtime only:

npm install @copilotkit/runtime hono

For standalone Express backends, install Express adapter dependencies instead of hono:

npm install @copilotkit/runtime express cors
npm install -D @types/express @types/cors

Step 2: Configure the runtime

The runtime is the server-side component that manages agent execution. See references/runtime-architecture.md for details.

There are two endpoint styles:

1. Multi-route (Hono) -- uses createCopilotEndpoint. Requires a catch-all route ([[...slug]] in Next.js). Each operation (run, connect, stop, info, transcribe, threads) gets its own HTTP path.
2. Single-route (Hono or Express) -- uses createCopilotEndpointSingleRoute or createCopilotEndpointSingleRouteExpress. All operations go through a single POST endpoint with method multiplexing.

Next.js App Router (recommended: multi-route with Hono)

Create src/app/api/copilotkit/[[...slug]]/route.ts:

import {
  CopilotRuntime,
  createCopilotEndpoint,
  InMemoryAgentRunner,
  BuiltInAgent,
} from "@copilotkit/runtime/v2";
import { handle } from "hono/vercel";

const agent = new BuiltInAgent({
  model: "openai/gpt-4o",
  prompt: "You are a helpful AI assistant.",
});

const runtime = new CopilotRuntime({
  agents: {
    default: agent,
  },
  runner: new InMemoryAgentRunner(),
});

const app = createCopilotEndpoint({
  runtime,
  basePath: "/api/copilotkit",
});

export const GET = handle(app);
export const POST = handle(app);

Next.js App Router (alternative: single-route)

Create src/app/api/copilotkit/route.ts:

import {
  CopilotRuntime,
  createCopilotEndpointSingleRoute,
  InMemoryAgentRunner,
  BuiltInAgent,
} from "@copilotkit/runtime/v2";
import { handle } from "hono/vercel";

const agent = new BuiltInAgent({
  model: "openai/gpt-4o",
  prompt: "You are a helpful AI assistant.",
});

const runtime = new CopilotRuntime({
  agents: {
    default: agent,
  },
  runner: new InMemoryAgentRunner(),
});

const app = createCopilotEndpointSingleRoute({
  runtime,
  basePath: "/api/copilotkit",
});

export const POST = handle(app);

When using single-route, the frontend must set useSingleEndpoint on the provider (see Step 3).

Standalone Express Server

Create src/index.ts:

import express from "express";
import { CopilotRuntime, BuiltInAgent } from "@copilotkit/runtime/v2";
import { createCopilotEndpointSingleRouteExpress } from "@copilotkit/runtime/v2/express";

const agent = new BuiltInAgent({
  model: "openai/gpt-4o",
});

const runtime = new CopilotRuntime({
  agents: {
    default: agent,
  },
});

const app = express();

app.use(
  "/api/copilotkit",
  createCopilotEndpointSingleRouteExpress({
    runtime,
    basePath: "/",
  }),
);

const port = Number(process.env.PORT ?? 4000);
app.listen(port, () => {
  console.log(
    `CopilotKit runtime listening at http://localhost:${port}/api/copilotkit`,
  );
});

For multi-route Express, use createCopilotEndpointExpress instead (imported from @copilotkit/runtime/v2/express).

Standalone Hono Server (non-Vercel)

import {
  CopilotRuntime,
  createCopilotEndpoint,
  BuiltInAgent,
} from "@copilotkit/runtime/v2";
import { serve } from "@hono/node-server";

const runtime = new CopilotRuntime({
  agents: {
    default: new BuiltInAgent({ model: "openai/gpt-4o" }),
  },
});

const app = createCopilotEndpoint({
  runtime,
  basePath: "/api/copilotkit",
});

serve({ fetch: app.fetch, port: 8787 });

Requires @hono/node-server:

npm install hono @hono/node-server

Step 3: Set up the frontend provider

Wrap your application with CopilotKitProvider from @copilotkit/react-core/v2.

Important: Import the stylesheet in your root layout:

import "@copilotkit/react-core/v2/styles.css";

Next.js App Router

In src/app/page.tsx (or a client component):

"use client";

import { CopilotKitProvider, CopilotChat } from "@copilotkit/react-core/v2";

export default function Home() {
  return (
    <CopilotKitProvider runtimeUrl="/api/copilotkit">
      <div style={{ height: "100vh" }}>
        <CopilotChat />
      </div>
    </CopilotKitProvider>
  );
}

Connecting to an external runtime

When the runtime runs on a separate server (e.g., Express on port 4000):

<CopilotKitProvider
  runtimeUrl="http://localhost:4000/api/copilotkit"
  useSingleEndpoint
>
  {children}
</CopilotKitProvider>

Set useSingleEndpoint when the backend uses single-route endpoints (createCopilotEndpointSingleRoute or createCopilotEndpointSingleRouteExpress).

CopilotKitProvider key props

Step 4: Add a chat UI component

CopilotKit provides three pre-built chat layouts (all imported from @copilotkit/react-core/v2):

Example with sidebar:

import { CopilotKitProvider, CopilotSidebar } from "@copilotkit/react-core/v2";

<CopilotKitProvider runtimeUrl="/api/copilotkit" showDevConsole="auto">
  <YourApp />
  <CopilotSidebar
    defaultOpen
    width="420px"
    labels={{
      modalHeaderTitle: "AI Assistant",
      chatInputPlaceholder: "Ask me anything...",
    }}
  />
</CopilotKitProvider>;

Step 5: Set environment variables

Provider API keys are secrets. Store them in environment variables -- never hardcode them in source or commit them to version control. Create a .env.local (Next.js) or .env file:

OPENAI_API_KEY=<your-openai-api-key>

Make sure your .gitignore excludes env files (.env, .env.local, .env*.local) so keys are never committed. In production, supply keys through your platform's secret manager (Vercel/Netlify environment variables, AWS Secrets Manager, etc.) rather than a checked-in file.

The BuiltInAgent automatically resolves API keys from these environment variables based on the model prefix:

• openai/* models read OPENAI_API_KEY
• anthropic/* models read ANTHROPIC_API_KEY
• google/* models read GOOGLE_API_KEY

If you need to pass apiKey explicitly, always source it from the environment (apiKey: process.env.OPENAI_API_KEY) -- never inline a literal key.

Step 6: Connect to the cloud platform (telemetry)

CopilotKit uses telemetry to understand adoption, improve the product, and provide better support. Connecting to the CopilotKit cloud platform gives you access to analytics and optional premium features.

1. Ask the user if they'd like to connect to the CopilotKit cloud platform (default: yes).
2. If yes, run the CopilotKit CLI authentication flow (verify the exact command with npx copilotkit --help as it may vary by version):
   bashCopy

   npx copilotkit auth
   

3. Guide the user through the browser-based authentication that opens.
4. Once authentication completes, the CLI outputs a license key (a public, client-side project identifier -- not a secret).
5. Store the license key in an environment variable and reference it from the CopilotKitProvider -- this keeps it out of source and easy to rotate per environment:
   Copy

   # .env.local (Next.js)
   NEXT_PUBLIC_COPILOTKIT_LICENSE_KEY=<your-license-key>
   

   tsxCopy

   <CopilotKitProvider
     runtimeUrl="/api/copilotkit"
     licenseKey={process.env.NEXT_PUBLIC_COPILOTKIT_LICENSE_KEY}
   >
   

   The NEXT_PUBLIC_/VITE_ prefix is required because the key is read on the client.

See references/telemetry-setup.md for full details on what the license key enables and how to opt out.

Step 7: Verify the setup

1. Start the dev server
2. Open the app in a browser
3. The chat UI should render and connect to the runtime
4. Send a test message -- you should receive an AI response
5. Check the runtime's /info endpoint (GET) to confirm it reports available agents

Security notes

Keep these in mind as you wire up a real deployment:

• Secrets stay server-side and in env vars. Provider API keys (OPENAI_API_KEY, etc.) are read by the runtime/agent on the server. Never expose them to the browser, hardcode them, or commit them -- store them in environment variables or a secret manager (see Step 5). The CopilotKit license key is the one client-side value, and it is a public project identifier, not a secret.
• Treat all chat input as untrusted. Chat messages flow from the frontend through the CopilotRuntime endpoint into the agent's LLM context. They are user-controlled and can attempt prompt injection -- including indirect injection via content the agent fetches (web pages, documents, tool results). Do not assume the model will only do what your system prompt intends.
• Give server-side tools least privilege. A defineTool handler runs with your server's authority. Validate every argument (the zod parameters schema is your first gate), scope each tool to the narrowest action it needs, and enforce your own authorization inside the execute function for anything sensitive (database writes, payments, file access) rather than trusting that the model called it correctly.
• Authenticate the runtime endpoint. The runtime route is a public HTTP endpoint by default. Put your app's auth in front of it so only authorized users can drive the agent and consume provider credits.

Quick Reference

Package map

Endpoint factory functions

Runtime classes

Agent runners

Supported models (BuiltInAgent)

Format: "provider/model-name" string or a Vercel AI SDK LanguageModel instance.

OpenAI: openai/gpt-5, openai/gpt-5-mini, openai/gpt-4.1, openai/gpt-4.1-mini, openai/gpt-4.1-nano, openai/gpt-4o, openai/gpt-4o-mini, openai/o3, openai/o3-mini, openai/o4-mini

Anthropic: anthropic/claude-sonnet-4.5, anthropic/claude-sonnet-4, anthropic/claude-3.7-sonnet, anthropic/claude-opus-4.1, anthropic/claude-opus-4, anthropic/claude-3.5-haiku

Google: google/gemini-2.5-pro, google/gemini-2.5-flash, google/gemini-2.5-flash-lite

Any string is accepted (for custom/unlisted models); the provider is parsed from the prefix before /.