copilot-sdk

作成者: github

CopilotのエージェントワークフローをPython、TypeScript、Go、.NETのアプリケーションに埋め込むためのプログラム可能なエージェントランタイム。Copilot CLIの背後にある本番環境でテスト済みの同じエンジンを公開し、ストリーミング応答、カスタムツール定義、マルチターン会話をサポート。4つの言語ランタイム(Node.js 18+、Python 3.8+、Go 1.21+、.NET 8.0+)をサポートし、すべてのプラットフォームで一貫したAPIを提供。MCPサーバーとの統合により、事前構築されたツール、カスタムエージェントペルソナなどを有効化。

npx skills add https://github.com/github/awesome-copilot --skill copilot-sdk

GitHub Copilot SDK

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.

Prerequisites

  1. GitHub Copilot CLI installed and authenticated (Installation guide)
  2. Language runtime: Node.js 18+, Python 3.8+, Go 1.21+, or .NET 8.0+

Verify CLI: copilot --version

Installation

Node.js/TypeScript

mkdir copilot-demo && cd copilot-demo
npm init -y --init-type module
npm install @github/copilot-sdk tsx

Python

pip install github-copilot-sdk

Go

mkdir copilot-demo && cd copilot-demo
go mod init copilot-demo
go get github.com/github/copilot-sdk/go

.NET

dotnet new console -n CopilotDemo && cd CopilotDemo
dotnet add package GitHub.Copilot.SDK

Quick Start

TypeScript

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

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

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

await client.stop();
process.exit(0);

Run: npx tsx index.ts

Python

import asyncio
from copilot import CopilotClient, PermissionHandler

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({
        "on_permission_request": PermissionHandler.approve_all,
        "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())

Go

package main

import (
    "fmt"
    "log"
    "os"
    copilot "github.com/github/copilot-sdk/go"
)

func main() {
    client := copilot.NewClient(nil)
    if err := client.Start(); err != nil {
        log.Fatal(err)
    }
    defer client.Stop()

    session, err := client.CreateSession(&copilot.SessionConfig{
        OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
        Model:               "gpt-4.1",
    })
    if err != nil {
        log.Fatal(err)
    }

    response, err := session.SendAndWait(copilot.MessageOptions{Prompt: "What is 2 + 2?"}, 0)
    if err != nil {
        log.Fatal(err)
    }

    fmt.Println(*response.Data.Content)
    os.Exit(0)
}

.NET (C#)

using GitHub.Copilot.SDK;

await using var client = new CopilotClient();
await using var session = await client.CreateSessionAsync(new SessionConfig
{
    OnPermissionRequest = PermissionHandler.ApproveAll,
    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, approveAll, SessionEvent } from "@github/copilot-sdk";

const client = new CopilotClient();
const session = await client.createSession({
    onPermissionRequest: approveAll,
    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, PermissionHandler
from copilot.generated.session_events import SessionEventType

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({
        "on_permission_request": PermissionHandler.approve_all,
        "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{
	OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
    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
{
    OnPermissionRequest = PermissionHandler.ApproveAll,
    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:

  1. What the tool does (description)
  2. What parameters it needs (schema)
  3. What code to run (handler)

TypeScript (JSON Schema)

import { CopilotClient, approveAll, 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({
    onPermissionRequest: approveAll,
    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, PermissionHandler
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({
        "on_permission_request": PermissionHandler.approve_all,
        "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{
	OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
    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
{
    OnPermissionRequest = PermissionHandler.ApproveAll,
    Model = "gpt-4.1",
    Streaming = true,
    Tools = [getWeather],
});

How Tools Work

When Copilot decides to call your tool:

  1. Copilot sends a tool call request with the parameters
  2. The SDK runs your handler function
  3. The result is sent back to Copilot
  4. 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, approveAll, 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({
    onPermissionRequest: approveAll,
    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, PermissionHandler
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({
        "on_permission_request": PermissionHandler.approve_all,
        "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:

TypeScript

const session = await client.createSession({
    onPermissionRequest: approveAll,
    model: "gpt-4.1",
    mcpServers: {
        github: {
            type: "http",
            url: "https://api.githubcopilot.com/mcp/",
        },
    },
});

Python

session = await client.create_session({
    "on_permission_request": PermissionHandler.approve_all,
    "model": "gpt-4.1",
    "mcp_servers": {
        "github": {
            "type": "http",
            "url": "https://api.githubcopilot.com/mcp/",
        },
    },
})

Go

session, _ := client.CreateSession(&copilot.SessionConfig{
	OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
    Model: "gpt-4.1",
    MCPServers: map[string]copilot.MCPServerConfig{
        "github": {
            "type": "http",
            "url": "https://api.githubcopilot.com/mcp/",
        },
    },
})

.NET

await using var session = await client.CreateSessionAsync(new SessionConfig
{
    OnPermissionRequest = PermissionHandler.ApproveAll,
    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({
    onPermissionRequest: approveAll,
    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({
    "on_permission_request": PermissionHandler.approve_all,
    "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({
    onPermissionRequest: approveAll,
    model: "gpt-4.1",
    systemMessage: {
        content: "You are a helpful assistant for our engineering team. Always be concise.",
    },
});

Python

session = await client.create_session({
    "on_permission_request": PermissionHandler.approve_all,
    "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.

Start CLI in Server Mode

copilot --server --port 4321

Connect SDK to External Server

TypeScript

const client = new CopilotClient({
    cliUrl: "localhost:4321"
});

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

Python

client = CopilotClient({
    "cli_url": "localhost:4321"
})
await client.start()

session = await client.create_session({
    "on_permission_request": PermissionHandler.approve_all,
    "model": "gpt-4.1",
})

Go

client := copilot.NewClient(&copilot.ClientOptions{
    CLIUrl: "localhost:4321",
})

if err := client.Start(); err != nil {
    log.Fatal(err)
}

session, _ := client.CreateSession(&copilot.SessionConfig{
	OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
	Model:               "gpt-4.1",
})

.NET

using var client = new CopilotClient(new CopilotClientOptions
{
    CliUrl = "localhost:4321"
});

await using var session = await client.CreateSessionAsync(new SessionConfig
{
    OnPermissionRequest = PermissionHandler.ApproveAll,
    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

EventDescription
user.messageUser input added
assistant.messageComplete model response
assistant.message_deltaStreaming response chunk
assistant.reasoningModel reasoning (model-dependent)
assistant.reasoning_deltaStreaming reasoning chunk
tool.execution_startTool invocation started
tool.execution_completeTool execution finished
session.idleNo active processing
session.errorError occurred

Client Configuration

OptionDescriptionDefault
cliPathPath to Copilot CLI executableSystem PATH
cliUrlConnect to existing server (e.g., "localhost:4321")None
portServer communication portRandom
useStdioUse stdio transport instead of TCPtrue
logLevelLogging verbosity"info"
autoStartLaunch server automaticallytrue
autoRestartRestart on crashestrue
cwdWorking directory for CLI processInherited

Session Configuration

OptionDescription
modelLLM to use ("gpt-4.1", "claude-sonnet-4.5", etc.)
sessionIdCustom session identifier
toolsCustom tool definitions
mcpServersMCP server connections
customAgentsCustom agent personas
systemMessageOverride default system prompt
streamingEnable incremental response chunks
availableToolsWhitelist of permitted tools
excludedToolsBlacklist of disabled tools

Session Persistence

Save and resume conversations across restarts:

Create with Custom ID

const session = await client.createSession({
    onPermissionRequest: approveAll,
    sessionId: "user-123-conversation",
    model: "gpt-4.1"
});

Resume Session

const session = await client.resumeSession("user-123-conversation", { onPermissionRequest: approveAll });
await session.send({ prompt: "What did we discuss earlier?" });

List and Delete Sessions

const sessions = await client.listSessions();
await client.deleteSession("old-session-id");

Error Handling

try {
    const client = new CopilotClient();
    const session = await client.createSession({
        onPermissionRequest: approveAll,
        model: "gpt-4.1",
    });
    const response = await session.sendAndWait(
        { prompt: "Hello!" },
        30000 // timeout in ms
    );
} catch (error) {
    if (error.code === "ENOENT") {
        console.error("Copilot CLI not installed");
    } else if (error.code === "ECONNREFUSED") {
        console.error("Cannot connect to Copilot server");
    } else {
        console.error("Error:", error.message);
    }
} finally {
    await client.stop();
}

Graceful Shutdown

process.on("SIGINT", async () => {
    console.log("Shutting down...");
    await client.stop();
    process.exit(0);
});

Common Patterns

Multi-turn Conversation

const session = await client.createSession({
    onPermissionRequest: approveAll,
    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"

File Attachments

await session.send({
    prompt: "Analyze this file",
    attachments: [{
        type: "file",
        path: "./data.csv",
        displayName: "Sales Data"
    }]
});

Abort Long Operations

const timeoutId = setTimeout(() => {
    session.abort();
}, 60000);

session.on((event) => {
    if (event.type === "session.idle") {
        clearTimeout(timeoutId);
    }
});

Available Models

Query available models at runtime:

const models = await client.getModels();
// Returns: ["gpt-4.1", "gpt-4o", "claude-sonnet-4.5", ...]

Best Practices

  1. Always cleanup: Use try-finally or defer to ensure client.stop() is called
  2. Set timeouts: Use sendAndWait with timeout for long operations
  3. Handle events: Subscribe to error events for robust error handling
  4. Use streaming: Enable streaming for better UX on long responses
  5. Persist sessions: Use custom session IDs for multi-turn conversations
  6. Define clear tools: Write descriptive tool names and descriptions

Architecture

Your Application
       |
  SDK Client
       | JSON-RPC
  Copilot CLI (server mode)
       |
  GitHub (models, auth)

The SDK manages the CLI process lifecycle automatically. All communication happens via JSON-RPC over stdio or TCP.

Resources

Status

This SDK is in Technical Preview and may have breaking changes. Not recommended for production use yet.

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agent-governance
github
宣言的なポリシー、意図分類、および監査証跡により、AIエージェントのツールアクセスと動作を制御します。構成可能なガバナンスポリシーは、許可/ブロックされたツール、コンテンツフィルター、レート制限、承認要件を定義し、コードではなく設定として保存されます。セマンティック意図分類は、パターンベースのシグナルを使用して、ツール実行前に危険なプロンプト(データ流出、権限昇格、プロンプトインジェクション)を検出します。ツールレベルのガバナンスデコレーターは、関数にポリシーを適用します...
official