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Microsoft Agent Framework supports creating agents that use the GitHub Copilot SDK as their backend. GitHub Copilot agents provide access to powerful coding-oriented AI capabilities, including shell command execution, file operations, URL fetching, and Model Context Protocol (MCP) server integration.
Important
GitHub Copilot agents require the GitHub Copilot CLI to be installed and authenticated. For security, it is recommended to run agents with shell or file permissions in a containerized environment (Docker/Dev Container).
Getting Started
Add the required NuGet packages to your project.
dotnet add package Microsoft.Agents.AI.GitHub.Copilot --prerelease
Create a GitHub Copilot Agent
As a first step, create a CopilotClient and start it. Then use the AsAIAgent extension method to create an agent.
using GitHub.Copilot.SDK;
using Microsoft.Agents.AI;
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
AIAgent agent = copilotClient.AsAIAgent();
Console.WriteLine(await agent.RunAsync("What is Microsoft Agent Framework?"));
With Tools and Instructions
You can provide function tools and custom instructions when creating the agent:
using GitHub.Copilot.SDK;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
AIFunction weatherTool = AIFunctionFactory.Create((string location) =>
{
return $"The weather in {location} is sunny with a high of 25C.";
}, "GetWeather", "Get the weather for a given location.");
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
AIAgent agent = copilotClient.AsAIAgent(
tools: [weatherTool],
instructions: "You are a helpful weather agent.");
Console.WriteLine(await agent.RunAsync("What's the weather like in Seattle?"));
Agent Features
Streaming Responses
Get responses as they are generated:
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
AIAgent agent = copilotClient.AsAIAgent();
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("Tell me a short story."))
{
Console.Write(update);
}
Console.WriteLine();
Session Management
Maintain conversation context across multiple interactions using sessions:
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
await using GitHubCopilotAgent agent = new(
copilotClient,
instructions: "You are a helpful assistant. Keep your answers short.");
AgentSession session = await agent.CreateSessionAsync();
// First turn
await agent.RunAsync("My name is Alice.", session);
// Second turn - agent remembers the context
AgentResponse response = await agent.RunAsync("What is my name?", session);
Console.WriteLine(response); // Should mention "Alice"
Permissions
By default, the agent cannot execute shell commands, read/write files, or fetch URLs. To enable these capabilities, provide a permission handler via SessionConfig:
static Task<PermissionRequestResult> PromptPermission(
PermissionRequest request, PermissionInvocation invocation)
{
Console.WriteLine($"\n[Permission Request: {request.Kind}]");
Console.Write("Approve? (y/n): ");
string? input = Console.ReadLine()?.Trim().ToUpperInvariant();
string kind = input is "Y" or "YES" ? "approved" : "denied-interactively-by-user";
return Task.FromResult(new PermissionRequestResult { Kind = kind });
}
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
SessionConfig sessionConfig = new()
{
OnPermissionRequest = PromptPermission,
};
AIAgent agent = copilotClient.AsAIAgent(sessionConfig);
Console.WriteLine(await agent.RunAsync("List all files in the current directory"));
MCP Servers
Connect to local (stdio) or remote (HTTP) MCP servers for extended capabilities:
await using CopilotClient copilotClient = new();
await copilotClient.StartAsync();
SessionConfig sessionConfig = new()
{
OnPermissionRequest = PromptPermission,
McpServers = new Dictionary<string, object>
{
// Local stdio server
["filesystem"] = new McpLocalServerConfig
{
Type = "stdio",
Command = "npx",
Args = ["-y", "@modelcontextprotocol/server-filesystem", "."],
Tools = ["*"],
},
// Remote HTTP server
["microsoft-learn"] = new McpRemoteServerConfig
{
Type = "http",
Url = "https://learn.microsoft.com/api/mcp",
Tools = ["*"],
},
},
};
AIAgent agent = copilotClient.AsAIAgent(sessionConfig);
Console.WriteLine(await agent.RunAsync("Search Microsoft Learn for 'Azure Functions' and summarize the top result"));
Using the Agent
The agent is a standard AIAgent and supports all standard AIAgent operations.
For more information on how to run and interact with agents, see the Agent getting started tutorials.
Prerequisites
Install the Microsoft Agent Framework GitHub Copilot package.
pip install agent-framework-github-copilot --pre
Configuration
The agent can be optionally configured using the following environment variables:
| Variable | Description |
|---|---|
GITHUB_COPILOT_CLI_PATH |
Path to the Copilot CLI executable |
GITHUB_COPILOT_MODEL |
Model to use (e.g., gpt-5, claude-sonnet-4) |
GITHUB_COPILOT_TIMEOUT |
Request timeout in seconds |
GITHUB_COPILOT_LOG_LEVEL |
CLI log level |
Getting Started
Import the required classes from Agent Framework:
import asyncio
from agent_framework.github import GitHubCopilotAgent, GitHubCopilotOptions
Create a GitHub Copilot Agent
Basic Agent Creation
The simplest way to create a GitHub Copilot agent:
async def basic_example():
agent = GitHubCopilotAgent(
default_options={"instructions": "You are a helpful assistant."},
)
async with agent:
result = await agent.run("What is Microsoft Agent Framework?")
print(result)
With Explicit Configuration
You can provide explicit configuration through default_options:
async def explicit_config_example():
agent = GitHubCopilotAgent(
default_options={
"instructions": "You are a helpful assistant.",
"model": "gpt-5",
"timeout": 120,
},
)
async with agent:
result = await agent.run("What can you do?")
print(result)
Agent Features
Function Tools
Equip your agent with custom functions:
from typing import Annotated
from pydantic import Field
def get_weather(
location: Annotated[str, Field(description="The location to get the weather for.")],
) -> str:
"""Get the weather for a given location."""
return f"The weather in {location} is sunny with a high of 25C."
async def tools_example():
agent = GitHubCopilotAgent(
default_options={"instructions": "You are a helpful weather agent."},
tools=[get_weather],
)
async with agent:
result = await agent.run("What's the weather like in Seattle?")
print(result)
Streaming Responses
Get responses as they are generated for better user experience:
async def streaming_example():
agent = GitHubCopilotAgent(
default_options={"instructions": "You are a helpful assistant."},
)
async with agent:
print("Agent: ", end="", flush=True)
async for chunk in agent.run_stream("Tell me a short story."):
if chunk.text:
print(chunk.text, end="", flush=True)
print()
Thread Management
Maintain conversation context across multiple interactions:
async def thread_example():
agent = GitHubCopilotAgent(
default_options={"instructions": "You are a helpful assistant."},
)
async with agent:
thread = agent.get_new_thread()
# First interaction
result1 = await agent.run("My name is Alice.", thread=thread)
print(f"Agent: {result1}")
# Second interaction - agent remembers the context
result2 = await agent.run("What's my name?", thread=thread)
print(f"Agent: {result2}") # Should remember "Alice"
Permissions
By default, the agent cannot execute shell commands, read/write files, or fetch URLs. To enable these capabilities, provide a permission handler:
from copilot.types import PermissionRequest, PermissionRequestResult
def prompt_permission(
request: PermissionRequest, context: dict[str, str]
) -> PermissionRequestResult:
kind = request.get("kind", "unknown")
print(f"\n[Permission Request: {kind}]")
response = input("Approve? (y/n): ").strip().lower()
if response in ("y", "yes"):
return PermissionRequestResult(kind="approved")
return PermissionRequestResult(kind="denied-interactively-by-user")
async def permissions_example():
agent = GitHubCopilotAgent(
default_options={
"instructions": "You are a helpful assistant that can execute shell commands.",
"on_permission_request": prompt_permission,
},
)
async with agent:
result = await agent.run("List the Python files in the current directory")
print(result)
MCP Servers
Connect to local (stdio) or remote (HTTP) MCP servers for extended capabilities:
from copilot.types import MCPServerConfig
async def mcp_example():
mcp_servers: dict[str, MCPServerConfig] = {
# Local stdio server
"filesystem": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", "."],
"tools": ["*"],
},
# Remote HTTP server
"microsoft-learn": {
"type": "http",
"url": "https://learn.microsoft.com/api/mcp",
"tools": ["*"],
},
}
agent = GitHubCopilotAgent(
default_options={
"instructions": "You are a helpful assistant with access to the filesystem and Microsoft Learn.",
"on_permission_request": prompt_permission,
"mcp_servers": mcp_servers,
},
)
async with agent:
result = await agent.run("Search Microsoft Learn for 'Azure Functions' and summarize the top result")
print(result)
Using the Agent
The agent is a standard BaseAgent and supports all standard agent operations.
For more information on how to run and interact with agents, see the Agent getting started tutorials.