Eduard van Valkenburg 9c57680f00 Python: Add header_provider to Streamable HTTP MCP servers (#4849)
* Python: Add header_provider to MCPStreamableHTTPTool (#4808)

Add a header_provider callback parameter to MCPStreamableHTTPTool that
enables injecting dynamic per-request HTTP headers from runtime kwargs
(originating from FunctionInvocationContext.kwargs set in agent middleware).

The implementation uses contextvars and httpx event hooks to ensure headers
are task-local and safe for concurrent tool calls:

- header_provider receives the runtime kwargs dict and returns headers
- call_tool sets a ContextVar before delegating to MCPTool.call_tool
- An httpx request event hook reads from the ContextVar and injects headers

Example usage:
    mcp_tool = MCPStreamableHTTPTool(
        name="web-api",
        url="https://api.example.com/mcp",
        header_provider=lambda kwargs: {
            "X-Auth-Token": kwargs.get("auth_token", ""),
        },
    )

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address review feedback for #4808: Python: [Bug]: Unable to pass AgentContext to MCPStreamableHTTPTool

* Add test for header_provider via FunctionTool.invoke with FunctionInvocationContext

Addresses PR review comment: exercises the full pipeline from
FunctionInvocationContext.kwargs through FunctionTool.invoke to
MCPStreamableHTTPTool.call_tool and header_provider, rather than
testing call_tool in isolation.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address review feedback for #4808: review comment fixes

* Fix streamable MCP transport defaults

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix Azure AI test client mocks

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix MCP runtime kwarg regressions

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Stabilize MCP tool runtime kwargs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Use context kwargs in MCP wrappers

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* updated mcp samples

* fix link

---------

Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
9c57680f00 · 2026-03-31 17:23:49 +00:00
1,784 Commits
2026-03-31 15:20:35 +00:00
2025-10-30 20:29:01 +00:00
2025-04-28 12:54:43 -07:00
2025-04-28 12:54:42 -07:00

Microsoft Agent Framework

Welcome to Microsoft Agent Framework!

Microsoft Azure AI Foundry Discord MS Learn Documentation PyPI NuGet

Welcome to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration.

Watch the full Agent Framework introduction (30 min)

Watch the full Agent Framework introduction (30 min)

📋 Getting Started

📦 Installation

Python

pip install agent-framework --pre
# This will install all sub-packages, see `python/packages` for individual packages.
# It may take a minute on first install on Windows.

.NET

dotnet add package Microsoft.Agents.AI

📚 Documentation

Still have questions? Join our weekly office hours or ask questions in our Discord channel to get help from the team and other users.

Highlights

  • Graph-based Workflows: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
  • AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
  • DevUI: Interactive developer UI for agent development, testing, and debugging workflows

See the DevUI in action

See the DevUI in action (1 min)

💬 We want your feedback!

Quickstart

Basic Agent - Python

Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework

# pip install agent-framework --pre
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential


async def main():
    # Initialize a chat agent with Azure OpenAI Responses
    # the endpoint, deployment name, and api version can be set via environment variables
    # or they can be passed in directly to the AzureOpenAIResponsesClient constructor
    agent = AzureOpenAIResponsesClient(
        # endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
        # deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
        # api_version=os.environ["AZURE_OPENAI_API_VERSION"],
        # api_key=os.environ["AZURE_OPENAI_API_KEY"],  # Optional if using AzureCliCredential
        credential=AzureCliCredential(), # Optional, if using api_key
    ).as_agent(
        name="HaikuBot",
        instructions="You are an upbeat assistant that writes beautifully.",
    )

    print(await agent.run("Write a haiku about Microsoft Agent Framework."))

if __name__ == "__main__":
    asyncio.run(main())

Basic Agent - .NET

Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;

// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

Create a simple Agent, using Azure OpenAI Responses with token based auth, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
// dotnet add package Azure.Identity
// Use `az login` to authenticate with Azure CLI
using System.ClientModel.Primitives;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;

// Replace <resource> and gpt-4o-mini with your Azure OpenAI resource name and deployment name.
var agent = new OpenAIClient(
    new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"),
    new OpenAIClientOptions() { Endpoint = new Uri("https://<resource>.openai.azure.com/openai/v1") })
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

More Examples & Samples

Python

.NET

Contributor Resources

Important Notes

If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.

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