Embed Copilot's agentic workflows in any application using Python, TypeScript, Go, or .NET.
Overview
The GitHub Copilot SDK exposes the same engine behind Copilot CLI: a production-tested agent runtime you can invoke programmatically. No need to build your own orchestration - you define agent behavior, Copilot handles planning, tool invocation, file edits, and more.
using GitHub.Copilot.SDK;
await using var client = new CopilotClient();
await using var session = await client.CreateSessionAsync(new SessionConfig { Model = "gpt-4.1" });
var response = await session.SendAndWaitAsync(new MessageOptions { Prompt = "What is 2 + 2?" });
Console.WriteLine(response?.Data.Content);
Run: dotnet run
Streaming Responses
Enable real-time output for better UX:
TypeScript
import { CopilotClient, SessionEvent } from "@github/copilot-sdk";
const client = new CopilotClient();
const session = await client.createSession({
model: "gpt-4.1",
streaming: true,
});
session.on((event: SessionEvent) => {
if (event.type === "assistant.message_delta") {
process.stdout.write(event.data.deltaContent);
}
if (event.type === "session.idle") {
console.log(); // New line when done
}
});
await session.sendAndWait({ prompt: "Tell me a short joke" });
await client.stop();
process.exit(0);
Python
import asyncio
import sys
from copilot import CopilotClient
from copilot.generated.session_events import SessionEventType
async def main():
client = CopilotClient()
await client.start()
session = await client.create_session({
"model": "gpt-4.1",
"streaming": True,
})
def handle_event(event):
if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
sys.stdout.write(event.data.delta_content)
sys.stdout.flush()
if event.type == SessionEventType.SESSION_IDLE:
print()
session.on(handle_event)
await session.send_and_wait({"prompt": "Tell me a short joke"})
await client.stop()
asyncio.run(main())
Go
session, err := client.CreateSession(&copilot.SessionConfig{
Model: "gpt-4.1",
Streaming: true,
})
session.On(func(event copilot.SessionEvent) {
if event.Type == "assistant.message_delta" {
fmt.Print(*event.Data.DeltaContent)
}
if event.Type == "session.idle" {
fmt.Println()
}
})
_, err = session.SendAndWait(copilot.MessageOptions{Prompt: "Tell me a short joke"}, 0)
.NET
await using var session = await client.CreateSessionAsync(new SessionConfig
{
Model = "gpt-4.1",
Streaming = true,
});
session.On(ev =>
{
if (ev is AssistantMessageDeltaEvent deltaEvent)
Console.Write(deltaEvent.Data.DeltaContent);
if (ev is SessionIdleEvent)
Console.WriteLine();
});
await session.SendAndWaitAsync(new MessageOptions { Prompt = "Tell me a short joke" });
Custom Tools
Define tools that Copilot can invoke during reasoning. When you define a tool, you tell Copilot:
What the tool does (description)
What parameters it needs (schema)
What code to run (handler)
TypeScript (JSON Schema)
import { CopilotClient, defineTool, SessionEvent } from "@github/copilot-sdk";
const getWeather = defineTool("get_weather", {
description: "Get the current weather for a city",
parameters: {
type: "object",
properties: {
city: { type: "string", description: "The city name" },
},
required: ["city"],
},
handler: async (args: { city: string }) => {
const { city } = args;
// In a real app, call a weather API here
const conditions = ["sunny", "cloudy", "rainy", "partly cloudy"];
const temp = Math.floor(Math.random() * 30) + 50;
const condition = conditions[Math.floor(Math.random() * conditions.length)];
return { city, temperature: `${temp}°F`, condition };
},
});
const client = new CopilotClient();
const session = await client.createSession({
model: "gpt-4.1",
streaming: true,
tools: [getWeather],
});
session.on((event: SessionEvent) => {
if (event.type === "assistant.message_delta") {
process.stdout.write(event.data.deltaContent);
}
});
await session.sendAndWait({
prompt: "What's the weather like in Seattle and Tokyo?",
});
await client.stop();
process.exit(0);
Python (Pydantic)
import asyncio
import random
import sys
from copilot import CopilotClient
from copilot.tools import define_tool
from copilot.generated.session_events import SessionEventType
from pydantic import BaseModel, Field
class GetWeatherParams(BaseModel):
city: str = Field(description="The name of the city to get weather for")
@define_tool(description="Get the current weather for a city")
async def get_weather(params: GetWeatherParams) -> dict:
city = params.city
conditions = ["sunny", "cloudy", "rainy", "partly cloudy"]
temp = random.randint(50, 80)
condition = random.choice(conditions)
return {"city": city, "temperature": f"{temp}°F", "condition": condition}
async def main():
client = CopilotClient()
await client.start()
session = await client.create_session({
"model": "gpt-4.1",
"streaming": True,
"tools": [get_weather],
})
def handle_event(event):
if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
sys.stdout.write(event.data.delta_content)
sys.stdout.flush()
session.on(handle_event)
await session.send_and_wait({
"prompt": "What's the weather like in Seattle and Tokyo?"
})
await client.stop()
asyncio.run(main())
Go
type WeatherParams struct {
City string `json:"city" jsonschema:"The city name"`
}
type WeatherResult struct {
City string `json:"city"`
Temperature string `json:"temperature"`
Condition string `json:"condition"`
}
getWeather := copilot.DefineTool(
"get_weather",
"Get the current weather for a city",
func(params WeatherParams, inv copilot.ToolInvocation) (WeatherResult, error) {
conditions := []string{"sunny", "cloudy", "rainy", "partly cloudy"}
temp := rand.Intn(30) + 50
condition := conditions[rand.Intn(len(conditions))]
return WeatherResult{
City: params.City,
Temperature: fmt.Sprintf("%d°F", temp),
Condition: condition,
}, nil
},
)
session, _ := client.CreateSession(&copilot.SessionConfig{
Model: "gpt-4.1",
Streaming: true,
Tools: []copilot.Tool{getWeather},
})
.NET (Microsoft.Extensions.AI)
using GitHub.Copilot.SDK;
using Microsoft.Extensions.AI;
using System.ComponentModel;
var getWeather = AIFunctionFactory.Create(
([Description("The city name")] string city) =>
{
var conditions = new[] { "sunny", "cloudy", "rainy", "partly cloudy" };
var temp = Random.Shared.Next(50, 80);
var condition = conditions[Random.Shared.Next(conditions.Length)];
return new { city, temperature = $"{temp}°F", condition };
},
"get_weather",
"Get the current weather for a city"
);
await using var session = await client.CreateSessionAsync(new SessionConfig
{
Model = "gpt-4.1",
Streaming = true,
Tools = [getWeather],
});
How Tools Work
When Copilot decides to call your tool:
Copilot sends a tool call request with the parameters
The SDK runs your handler function
The result is sent back to Copilot
Copilot incorporates the result into its response
Copilot decides when to call your tool based on the user's question and your tool's description.
Interactive CLI Assistant
Build a complete interactive assistant:
TypeScript
import { CopilotClient, defineTool, SessionEvent } from "@github/copilot-sdk";
import * as readline from "readline";
const getWeather = defineTool("get_weather", {
description: "Get the current weather for a city",
parameters: {
type: "object",
properties: {
city: { type: "string", description: "The city name" },
},
required: ["city"],
},
handler: async ({ city }) => {
const conditions = ["sunny", "cloudy", "rainy", "partly cloudy"];
const temp = Math.floor(Math.random() * 30) + 50;
const condition = conditions[Math.floor(Math.random() * conditions.length)];
return { city, temperature: `${temp}°F`, condition };
},
});
const client = new CopilotClient();
const session = await client.createSession({
model: "gpt-4.1",
streaming: true,
tools: [getWeather],
});
session.on((event: SessionEvent) => {
if (event.type === "assistant.message_delta") {
process.stdout.write(event.data.deltaContent);
}
});
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
});
console.log("Weather Assistant (type 'exit' to quit)");
console.log("Try: 'What's the weather in Paris?'\n");
const prompt = () => {
rl.question("You: ", async (input) => {
if (input.toLowerCase() === "exit") {
await client.stop();
rl.close();
return;
}
process.stdout.write("Assistant: ");
await session.sendAndWait({ prompt: input });
console.log("\n");
prompt();
});
};
prompt();
Python
import asyncio
import random
import sys
from copilot import CopilotClient
from copilot.tools import define_tool
from copilot.generated.session_events import SessionEventType
from pydantic import BaseModel, Field
class GetWeatherParams(BaseModel):
city: str = Field(description="The name of the city to get weather for")
@define_tool(description="Get the current weather for a city")
async def get_weather(params: GetWeatherParams) -> dict:
conditions = ["sunny", "cloudy", "rainy", "partly cloudy"]
temp = random.randint(50, 80)
condition = random.choice(conditions)
return {"city": params.city, "temperature": f"{temp}°F", "condition": condition}
async def main():
client = CopilotClient()
await client.start()
session = await client.create_session({
"model": "gpt-4.1",
"streaming": True,
"tools": [get_weather],
})
def handle_event(event):
if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
sys.stdout.write(event.data.delta_content)
sys.stdout.flush()
session.on(handle_event)
print("Weather Assistant (type 'exit' to quit)")
print("Try: 'What's the weather in Paris?'\n")
while True:
try:
user_input = input("You: ")
except EOFError:
break
if user_input.lower() == "exit":
break
sys.stdout.write("Assistant: ")
await session.send_and_wait({"prompt": user_input})
print("\n")
await client.stop()
asyncio.run(main())
MCP Server Integration
Connect to MCP (Model Context Protocol) servers for pre-built tools. Connect to GitHub's MCP server for repository, issue, and PR access:
await using var session = await client.CreateSessionAsync(new SessionConfig
{
Model = "gpt-4.1",
McpServers = new Dictionary<string, McpServerConfig>
{
["github"] = new McpServerConfig
{
Type = "http",
Url = "https://api.githubcopilot.com/mcp/",
},
},
});
Custom Agents
Define specialized AI personas for specific tasks:
TypeScript
const session = await client.createSession({
model: "gpt-4.1",
customAgents: [{
name: "pr-reviewer",
displayName: "PR Reviewer",
description: "Reviews pull requests for best practices",
prompt: "You are an expert code reviewer. Focus on security, performance, and maintainability.",
}],
});
Python
session = await client.create_session({
"model": "gpt-4.1",
"custom_agents": [{
"name": "pr-reviewer",
"display_name": "PR Reviewer",
"description": "Reviews pull requests for best practices",
"prompt": "You are an expert code reviewer. Focus on security, performance, and maintainability.",
}],
})
System Message
Customize the AI's behavior and personality:
TypeScript
const session = await client.createSession({
model: "gpt-4.1",
systemMessage: {
content: "You are a helpful assistant for our engineering team. Always be concise.",
},
});
Python
session = await client.create_session({
"model": "gpt-4.1",
"system_message": {
"content": "You are a helpful assistant for our engineering team. Always be concise.",
},
})
External CLI Server
Run the CLI in server mode separately and connect the SDK to it. Useful for debugging, resource sharing, or custom environments.
using var client = new CopilotClient(new CopilotClientOptions
{
CliUrl = "localhost:4321"
});
await using var session = await client.CreateSessionAsync(new SessionConfig { Model = "gpt-4.1" });
Note: When cliUrl is provided, the SDK will not spawn or manage a CLI process - it only connects to the existing server.
Event Types
Event
Description
user.message
User input added
assistant.message
Complete model response
assistant.message_delta
Streaming response chunk
assistant.reasoning
Model reasoning (model-dependent)
assistant.reasoning_delta
Streaming reasoning chunk
tool.execution_start
Tool invocation started
tool.execution_complete
Tool execution finished
session.idle
No active processing
session.error
Error occurred
Client Configuration
Option
Description
Default
cliPath
Path to Copilot CLI executable
System PATH
cliUrl
Connect to existing server (e.g., "localhost:4321")
const session = await client.createSession({ model: "gpt-4.1" });
await session.sendAndWait({ prompt: "My name is Alice" });
await session.sendAndWait({ prompt: "What's my name?" });
// Response: "Your name is Alice"