name: github-copilot-sdk description: Comprehensive knowledge of GitHub Copilot SDK for embedding Copilot's agentic workflows in Python, TypeScript, Go, and .NET applications. Auto-activates for Copilot SDK integration, CopilotClient usage, session management, streaming responses, custom tools, and MCP server connections. version: 1.0.0 last_updated: 2025-01-25 source_urls:

• https://github.com/github/copilot-sdk
• https://github.com/github/awesome-copilot/blob/main/collections/copilot-sdk.md activation_keywords:
• copilot sdk
• github copilot sdk
• copilot client
• github copilot client
• copilot session
• copilot streaming
• copilot custom tools
• copilot mcp
• embed copilot
• copilot api auto_activate: true token_budget: 2000

GitHub Copilot SDK - Comprehensive Skill

Overview

The GitHub Copilot SDK enables developers to embed Copilot's agentic workflows programmatically in their applications. It exposes the same engine behind Copilot CLI as a production-tested agent runtime you can invoke from code.

When to Use the Copilot SDK

Use the Copilot SDK when:

• Building applications that need Copilot's AI capabilities
• Implementing custom AI assistants with tool-calling abilities
• Creating integrations that leverage Copilot's code understanding
• Connecting to MCP (Model Context Protocol) servers for standardized tools
• Need streaming responses in custom UIs

Don't use when:

• GitHub Copilot CLI is sufficient (use CLI directly)
• No programmatic integration needed (use Copilot in VS Code)
• Building simple chat without tools (use standard LLM API)

Language Support

Prerequisites

1. GitHub Copilot CLI installed and authenticated
2. Active Copilot subscription (free tier available with limits)

Quick Start

Minimal Example (TypeScript)

import { CopilotClient } from "@github/copilot-sdk";

const client = new CopilotClient();
const session = await client.createSession({ model: "gpt-4.1" });

const response = await session.sendAndWait({ prompt: "What is 2 + 2?" });
console.log(response?.data.content);

await client.stop();

Minimal Example (Python)

import asyncio
from copilot import CopilotClient

async def main():
    client = CopilotClient()
    await client.start()
    session = await client.create_session({"model": "gpt-4.1"})
    response = await session.send_and_wait({"prompt": "What is 2 + 2?"})
    print(response.data.content)
    await client.stop()

asyncio.run(main())

Add Streaming

const session = await client.createSession({
  model: "gpt-4.1",
  streaming: true,
});

session.on((event) => {
  if (event.type === "assistant.message_delta") {
    process.stdout.write(event.data.deltaContent);
  }
});

await session.sendAndWait({ prompt: "Tell me a joke" });

Add Custom Tool

import { defineTool } from "@github/copilot-sdk";

const getWeather = defineTool("get_weather", {
  description: "Get weather for a city",
  parameters: {
    type: "object",
    properties: {
      city: { type: "string", description: "City name" },
    },
    required: ["city"],
  },
  handler: async ({ city }) => ({
    city,
    temperature: `${Math.floor(Math.random() * 30) + 50}°F`,
    condition: "sunny",
  }),
});

const session = await client.createSession({
  model: "gpt-4.1",
  tools: [getWeather],
});

Core Concepts

Architecture

Your Application → SDK Client → JSON-RPC → Copilot CLI (server mode)

The SDK manages the CLI process lifecycle automatically or connects to an external CLI server.

Key Components

1. CopilotClient: Entry point - manages connection to Copilot CLI
2. Session: Conversation context with model, tools, and history
3. Tools: Custom functions Copilot can invoke
4. Events: Streaming responses and tool call notifications
5. MCP Integration: Connect to Model Context Protocol servers

Session Configuration

const session = await client.createSession({
  model: "gpt-4.1", // Model to use
  streaming: true, // Enable streaming
  tools: [myTool], // Custom tools
  mcpServers: {
    // MCP server connections
    github: {
      type: "http",
      url: "https://api.githubcopilot.com/mcp/",
    },
  },
  systemMessage: {
    // Custom system prompt
    content: "You are a helpful assistant.",
  },
  customAgents: [
    {
      // Custom agent personas
      name: "code-reviewer",
      displayName: "Code Reviewer",
      description: "Reviews code for best practices",
      prompt: "Focus on security and performance.",
    },
  ],
});

Navigation Guide

When to Read Supporting Files

reference.md - Read when you need:

• Complete API reference for all 4 languages
• All method signatures with parameters and return types
• Session configuration options
• Event types and handling
• External CLI server connection

examples.md - Read when you need:

• Working copy-paste code for all 4 languages
• Error handling patterns
• Multiple sessions management
• Interactive assistant implementation
• Custom agent definition examples

patterns.md - Read when you need:

• Production-ready architectural patterns
• Streaming UI integration
• MCP server integration patterns
• Rate limiting and retry patterns
• Structured output extraction

drift-detection.md - Read when you need:

• Understanding how this skill stays current
• Validation workflow
• Update procedures

Quick Reference

Common Event Types

Default Tools

The SDK operates in --allow-all mode by default, enabling:

• File system operations
• Git operations
• Web requests
• All first-party Copilot tools

Integration with Amplihack

Use the Copilot SDK to build custom agents within amplihack:

# Create Copilot-powered agent for specific domain
from copilot import CopilotClient

async def create_code_review_agent():
    client = CopilotClient()
    await client.start()
    session = await client.create_session({
        "model": "gpt-4.1",
        "streaming": True,
        "systemMessage": {
            "content": "You are an expert code reviewer."
        }
    })
    return session

Next Steps

1. Start Simple: Basic send/receive with default model
2. Add Streaming: Real-time responses for better UX
3. Add Tools: Custom functions for your domain
4. Connect MCP: Use GitHub MCP server for repo access
5. Build UI: Integrate into your application

For complete API details, see reference.md. For working code in all languages, see examples.md. For production patterns, see patterns.md.