How to integrate Heygen MCP with LlamaIndex

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Introduction

This guide walks you through connecting Heygen to LlamaIndex 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 LlamaIndex 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Heygen
  • Connect LlamaIndex to the Heygen MCP server
  • Build a Heygen-powered agent using LlamaIndex
  • Interact with Heygen through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Heygen account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Heygen

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Heygen access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called heygen_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["heygen"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Heygen actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Heygen actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, heygen)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Heygen tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Heygen database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Heygen

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Heygen, then start asking questions.

Complete Code

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

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["heygen"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Heygen actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Heygen actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Heygen to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Heygen tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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

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 LlamaIndex?

Yes, you can. LlamaIndex 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.

Used by agents from

Context
ASU
Letta
glean
HubSpot
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Altera
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Entelligence
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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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