copilot-sdk

name	copilot-sdk
description	Build applications powered by GitHub Copilot using the Copilot SDK. Use when creating programmatic integrations with Copilot across Node.js/TypeScript, Python, Go, or .NET. Covers session management, custom tools, streaming, hooks, MCP servers, BYOK providers, session persistence, and custom agents. Requires GitHub Copilot CLI installed and a GitHub Copilot subscription (unless using BYOK).

GitHub Copilot SDK

Build applications that programmatically interact with GitHub Copilot. The SDK wraps the Copilot CLI via JSON-RPC, providing session management, custom tools, hooks, MCP server integration, and streaming across Node.js, Python, Go, and .NET.

Prerequisites

• GitHub Copilot CLI installed and authenticated (copilot --version to verify)
• GitHub Copilot subscription (Individual, Business, or Enterprise) — not required for BYOK
• Runtime: Node.js 18+ / Python 3.8+ / Go 1.21+ / .NET 8.0+

Installation

Language	Package	Install
Node.js	@github/copilot-sdk	npm install @github/copilot-sdk
Python	github-copilot-sdk	pip install github-copilot-sdk
Go	github.com/github/copilot-sdk/go	go get github.com/github/copilot-sdk/go
.NET	GitHub.Copilot.SDK	dotnet add package GitHub.Copilot.SDK

---

Core Pattern: Client → Session → Message

All SDK usage follows this pattern: create a client, create a session, send messages.

Node.js / 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();

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())

Go

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

session, _ := client.CreateSession(ctx, &copilot.SessionConfig{Model: "gpt-4.1"})
response, _ := session.SendAndWait(ctx, copilot.MessageOptions{Prompt: "What is 2 + 2?"})
fmt.Println(*response.Data.Content)

.NET

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);

---

Streaming Responses

Enable real-time output by setting streaming: true and subscribing to delta events.

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

session.on("assistant.message_delta", (event) => {
    process.stdout.write(event.data.deltaContent);
});
session.on("session.idle", () => console.log());

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

Python equivalent:

from copilot.generated.session_events import SessionEventType

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()

session.on(handle_event)
await session.send_and_wait({"prompt": "Tell me a joke"})

Event Subscription

Method	Description
on(handler)	Subscribe to all events; returns unsubscribe function
on(eventType, handler)	Subscribe to specific event type (Node.js only)

---

Custom Tools

Define tools that Copilot can call to extend its capabilities.

Node.js

import { CopilotClient, defineTool } 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 ({ city }) => ({ city, temperature: "72°F", condition: "sunny" }),
});

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

Python

from copilot.tools import define_tool
from pydantic import BaseModel, Field

class GetWeatherParams(BaseModel):
    city: str = Field(description="The city name")

@define_tool(description="Get the current weather for a city")
async def get_weather(params: GetWeatherParams) -> dict:
    return {"city": params.city, "temperature": "72°F", "condition": "sunny"}

session = await client.create_session({"model": "gpt-4.1", "tools": [get_weather]})

Go

type WeatherParams struct {
    City string `json:"city" jsonschema:"The city name"`
}

getWeather := copilot.DefineTool("get_weather", "Get weather for a city",
    func(params WeatherParams, inv copilot.ToolInvocation) (WeatherResult, error) {
        return WeatherResult{City: params.City, Temperature: "72°F"}, nil
    },
)

session, _ := client.CreateSession(ctx, &copilot.SessionConfig{
    Model: "gpt-4.1",
    Tools: []copilot.Tool{getWeather},
})

.NET

var getWeather = AIFunctionFactory.Create(
    ([Description("The city name")] string city) => new { city, temperature = "72°F" },
    "get_weather", "Get the current weather for a city");

await using var session = await client.CreateSessionAsync(new SessionConfig {
    Model = "gpt-4.1", Tools = [getWeather],
});

---

Hooks

Intercept and customize session behavior at key lifecycle points.

Hook	Trigger	Use Case
onPreToolUse	Before tool executes	Permission control, argument modification
onPostToolUse	After tool executes	Result transformation, logging
onUserPromptSubmitted	User sends message	Prompt modification, filtering
onSessionStart	Session begins	Add context, configure session
onSessionEnd	Session ends	Cleanup, analytics
onErrorOccurred	Error happens	Custom error handling, retry logic

Example: Tool Permission Control

const session = await client.createSession({
    hooks: {
        onPreToolUse: async (input) => {
            if (["shell", "bash"].includes(input.toolName)) {
                return { permissionDecision: "deny", permissionDecisionReason: "Shell access not permitted" };
            }
            return { permissionDecision: "allow" };
        },
    },
});

Pre-Tool Use Output

Field	Type	Description
permissionDecision	"allow" | "deny" | "ask"	Whether to allow the tool call
permissionDecisionReason	string	Explanation for deny/ask
modifiedArgs	object	Modified arguments to pass
additionalContext	string	Extra context for conversation
suppressOutput	boolean	Hide tool output from conversation

---

MCP Server Integration

Connect to MCP servers for pre-built tool capabilities.

Remote HTTP Server

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

Local Stdio Server

const session = await client.createSession({
    mcpServers: {
        filesystem: {
            type: "local",
            command: "npx",
            args: ["-y", "@modelcontextprotocol/server-filesystem", "/allowed/path"],
            tools: ["*"],
        },
    },
});

MCP Config Fields

Field	Type	Description
type	"local" | "http"	Server transport type
command	string	Executable path (local)
args	string[]	Command arguments (local)
url	string	Server URL (http)
tools	string[]	["*"] or specific tool names
env	object	Environment variables
cwd	string	Working directory (local)
timeout	number	Timeout in milliseconds

---

Authentication

Methods (Priority Order)

1. Explicit token — githubToken in constructor
2. Environment variables — COPILOT_GITHUB_TOKEN → GH_TOKEN → GITHUB_TOKEN
3. Stored OAuth — From copilot auth login
4. GitHub CLI — gh auth credentials

Programmatic Token

const client = new CopilotClient({ githubToken: process.env.GITHUB_TOKEN });

BYOK (Bring Your Own Key)

Use your own API keys — no Copilot subscription required.

const session = await client.createSession({
    model: "gpt-5.2-codex",
    provider: {
        type: "openai",
        baseUrl: "https://your-resource.openai.azure.com/openai/v1/",
        wireApi: "responses",
        apiKey: process.env.FOUNDRY_API_KEY,
    },
});

Provider	Type	Notes
OpenAI	"openai"	OpenAI API and compatible endpoints
Azure OpenAI	"azure"	Native Azure endpoints (don't include /openai/v1)
Azure AI Foundry	"openai"	OpenAI-compatible Foundry endpoints
Anthropic	"anthropic"	Claude models
Ollama	"openai"	Local models, no API key needed

Wire API: Use "responses" for GPT-5 series, "completions" (default) for others.

---

Session Persistence

Resume sessions across restarts by providing your own session ID.

// Create with explicit ID
const session = await client.createSession({
    sessionId: "user-123-task-456",
    model: "gpt-4.1",
});

// Resume later
const resumed = await client.resumeSession("user-123-task-456");
await resumed.sendAndWait({ prompt: "What did we discuss?" });

Session management:

const sessions = await client.listSessions();          // List all
await client.deleteSession("user-123-task-456");       // Delete
await session.destroy();                                // Destroy active

BYOK sessions: Must re-provide provider config on resume (keys are not persisted).

Infinite Sessions

For long-running workflows that may exceed context limits:

const session = await client.createSession({
    infiniteSessions: {
        enabled: true,
        backgroundCompactionThreshold: 0.80,
        bufferExhaustionThreshold: 0.95,
    },
});

---

Custom Agents

Define specialized AI personas:

const session = await client.createSession({
    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.",
    }],
});

---

System Message

Control AI behavior and personality:

const session = await client.createSession({
    systemMessage: { content: "You are a helpful assistant. Always be concise." },
});

---

Skills Integration

Load skill directories to extend Copilot's capabilities:

const session = await client.createSession({
    skillDirectories: ["./skills/code-review", "./skills/documentation"],
    disabledSkills: ["experimental-feature"],
});

---

Permission & Input Handlers

Handle tool permissions and user input requests programmatically:

const session = await client.createSession({
    onPermissionRequest: async (request) => {
        // Auto-approve git commands only
        if (request.kind === "shell") {
            return { approved: request.command.startsWith("git") };
        }
        return { approved: true };
    },
    onUserInputRequest: async (request) => {
        // Handle ask_user tool calls
        return { response: "yes" };
    },
});

---

External CLI Server

Connect to a separately running CLI instead of auto-managing the process:

copilot --headless --port 4321

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

---

Client Configuration

Option	Type	Description
cliPath	string	Path to Copilot CLI executable
cliUrl	string	URL of external CLI server
githubToken	string	GitHub token for auth
useLoggedInUser	boolean	Use stored CLI credentials (default: true)
logLevel	string	"none" | "error" | "warning" | "info" | "debug"
autoRestart	boolean	Auto-restart CLI on crash (default: true)
useStdio	boolean	Use stdio transport (default: true)

Session Configuration

Option	Type	Description
model	string	Model to use (e.g., "gpt-4.1")
sessionId	string	Custom ID for resumable sessions
streaming	boolean	Enable streaming responses
tools	Tool[]	Custom tools
mcpServers	object	MCP server configurations
hooks	object	Session hooks
provider	object	BYOK provider config
customAgents	object[]	Custom agent definitions
systemMessage	object	System message override
skillDirectories	string[]	Directories to load skills from
disabledSkills	string[]	Skills to disable
reasoningEffort	string	Reasoning effort level
availableTools	string[]	Restrict available tools
excludedTools	string[]	Exclude specific tools
infiniteSessions	object	Auto-compaction config
workingDirectory	string	Working directory

---

Debugging

Enable debug logging to troubleshoot issues:

const client = new CopilotClient({ logLevel: "debug" });

Common issues:

• CLI not found → Install CLI or set cliPath
• Not authenticated → Run copilot auth login or provide githubToken
• Session not found → Don't use session after destroy()
• Connection refused → Check CLI process, enable autoRestart

---

Key API Summary

Language	Client	Session Create	Send	Stop
Node.js	new CopilotClient()	client.createSession()	session.sendAndWait()	client.stop()
Python	CopilotClient()	client.create_session()	session.send_and_wait()	client.stop()
Go	copilot.NewClient(nil)	client.CreateSession()	session.SendAndWait()	client.Stop()
.NET	new CopilotClient()	client.CreateSessionAsync()	session.SendAndWaitAsync()	client.DisposeAsync()

References

• GitHub Copilot SDK
• Copilot CLI Installation
• MCP Protocol Specification

---

🧠 AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Hybrid Memory Integration (Qdrant + BM25)

Before executing complex tasks with this skill:

python3 execution/memory_manager.py auto --query "<task summary>"

Decision Tree:

• Cache hit? Use cached response directly — no need to re-process.
• Memory match? Inject context_chunks into your reasoning.
• No match? Proceed normally, then store results:

python3 execution/memory_manager.py store \
  --content "Description of what was decided/solved" \
  --type decision \
  --tags copilot-sdk <relevant-tags>

Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.

Agent Team Collaboration

• Strategy: This skill communicates via the shared memory system.
• Orchestration: Invoked by orchestrator via intelligent routing.
• Context Sharing: Always read previous agent outputs from memory before starting.

Local LLM Support

When available, use local Ollama models for embedding and lightweight inference:

• Embeddings: nomic-embed-text via Qdrant memory system
• Lightweight analysis: Local models reduce API costs for repetitive patterns