How to integrate Heygen MCP with Autogen

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Introduction

This guide walks you through connecting Heygen to AutoGen using the Composio tool router. By the end, you'll have a working Heygen agent that can create a talking photo from my selfie, add new contacts to my video project, list all available streaming avatars for today, fetch details of my latest personalized video project through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Heygen account through Composio's Heygen MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Heygen
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Heygen tools
  • Run a live chat loop where you ask the agent to perform Heygen operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Heygen MCP server, and what's possible with it?

The Heygen MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Heygen account. It provides structured and secure access to your Heygen video platform, so your agent can perform actions like creating talking photos, managing video assets, personalizing video projects, and controlling streaming avatars on your behalf.

  • AI-powered video asset creation: Add new avatars, backgrounds, or other content elements directly into your Heygen library for use in video generation workflows.
  • Personalized video project management: Let your agent add contacts to personalized video projects and fetch detailed project information to streamline large-scale video personalization efforts.
  • Dynamic talking photo generation: Instantly create engaging talking photos from uploaded images, transforming static pictures into interactive, speaking content for marketing or educational use.
  • Real-time avatar streaming control: Retrieve a list of streaming avatars, generate streaming tokens, and manage live avatar sessions—including interrupting or monitoring ongoing streams for responsive, interactive experiences.
  • Audience insights and analytics: Fetch detailed audience engagement and preference data for personalized video campaigns, helping you optimize your content and targeting strategies.

Supported Tools & Triggers

Tools
Add new assetCreates a new asset in the heygen platform.
Add contact to personalized video projectThis endpoint allows you to add one or more contacts to a specific personalized video project in the heygen platform.
Retrieve audience video detailsRetrieves detailed information about the audience for personalized videos.
Fetch personalized video project detailRetrieves detailed information about a specific personalized video project in the heygen platform.
Post talking photo binary imageCreates a talking photo by processing an uploaded image file.
List streaming avatarsRetrieves a list of available avatars for streaming purposes in the heygen platform.
Create streaming token with expiryCreates a new streaming token for use with heygen's real-time avatar and voice chat services.
Post streaming ice candidatesThis endpoint is used to submit ice (interactive connectivity establishment) candidate information for a specific streaming session in the heygen platform.
Interrupt streaming sessionInterrupts an ongoing streaming session with an interactive avatar.
Retrieve streaming listRetrieves a list of active or available streaming sessions or content within the heygen platform.
Set streaming quality endpointInitiates a new streaming session with heygen, allowing users to start an avatar-based stream with specified quality settings.
Start streaming sessionInitiates a new streaming session for real-time communication in the heygen platform.
Stop streaming sessionThe streaming.
Post streaming task sessionThe streamingtask endpoint initiates a real-time speaking task for an ai-driven avatar within an active streaming session.
List avatars endpointRetrieves a list of available avatars from the heygen platform.
List talking photo entriesRetrieves a list of talking photos created using the heygen platform.
Delete videoThe video.
List videosRetrieves a list of videos associated with the user's account on the heygen platform.
Retrieve video statusRetrieves the current status of a video in the heygen platform.
List voice endpointsRetrieves a comprehensive list of all available voices in the heygen platform.
Add webhook endpointAdds a new webhook endpoint to receive real-time notifications for specified heygen events.
Delete webhook endpointDeletes a specific webhook endpoint from the heygen system.
List webhook endpointsRetrieves a list of all webhook endpoints configured for your heygen account.
List webhooksRetrieves a list of all webhooks configured for your heygen account.
Retrieve avatars collectionRetrieves a list of available avatars from the heygen platform.
Delete talking photo by idDeletes a specific talking photo from the heygen platform using its unique identifier.
Generate video template with variablesThis endpoint generates a customized video based on a pre-existing template using heygen's ai-driven platform.
Get template by idRetrieves a specific template from the heygen platform using its unique identifier.
Retrieve all templatesRetrieves a list of available avatar templates from the heygen platform.
Retrieve user remaining quotaRetrieves the current remaining quota for the authenticated user on the heygen platform.
Generate video with inputsGenerates a customized video using heygen's ai-driven platform.
Post video translate requestThe translatevideo endpoint enables the translation of video content from one language to another.
Retrieve video translation by idRetrieves the current status of a video translation job in the heygen platform.
Retrieve video translation target languagesRetrieves a list of all available target languages supported by heygen's video translation feature.
List available voicesRetrieves a list of available voice models and options that can be used with heygen's ai-driven video creation platform.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Heygen account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Heygen via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Heygen connections to use

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Heygen session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["heygen"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Heygen tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Heygen assistant agent with MCP tools
    agent = AssistantAgent(
        name="heygen_assistant",
        description="An AI assistant that helps with Heygen operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Heygen tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Heygen related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Heygen tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Heygen and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Heygen session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["heygen"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Heygen assistant agent with MCP tools
        agent = AssistantAgent(
            name="heygen_assistant",
            description="An AI assistant that helps with Heygen operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Heygen related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Heygen through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Heygen, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Heygen MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Heygen MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Heygen MCP with Claude Agent SDK

Google ADK

Google ADK

Use Heygen MCP with Google ADK

LangChain

LangChain

Use Heygen MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Heygen MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Heygen MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Heygen MCP with LlamaIndex

CrewAI

CrewAI

Use Heygen MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Heygen MCP?

With a standalone Heygen MCP server, the agents and LLMs can only access a fixed set of Heygen tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Heygen and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Heygen tools.

Can I manage the permissions and scopes for Heygen while using Tool Router?

Yes, absolutely. You can configure which Heygen scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Heygen data and credentials are handled as safely as possible.

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