How to integrate Instagram MCP with Autogen

This guide walks you through connecting Instagram to AutoGen using the Composio tool router. By the end, you'll have a working Instagram agent that can get analytics for last week's posts, list your most recent instagram photos, fetch comments on your latest post through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Instagram account through Composio's Instagram MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Instagram logoInstagram
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Instagram is a social platform for sharing photos, videos, and stories with your audience. It helps brands and creators engage, grow, and analyze their online presence.

29 Tools

Introduction

This guide walks you through connecting Instagram to AutoGen using the Composio tool router. By the end, you'll have a working Instagram agent that can get analytics for last week's posts, list your most recent instagram photos, fetch comments on your latest post through natural language commands.

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

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

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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 Instagram
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Instagram tools
  • Run a live chat loop where you ask the agent to perform Instagram 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 Instagram MCP server, and what's possible with it?

The Instagram MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Instagram Business or Creator account. It provides structured and secure access to your Instagram content and analytics, so your agent can publish posts, analyze insights, fetch comments, manage conversations, and more—all on your behalf.

  • Automated post and carousel publishing: Let your agent draft and publish single-photo, video, or multi-image carousel posts to your feed with ease.
  • Real-time comments retrieval: Ask your agent to fetch and organize comments from any of your Instagram posts, making it simple to engage with your audience.
  • Insightful analytics and reporting: Request detailed insights on individual posts or your entire account, including impressions, reach, and engagement metrics.
  • Direct message conversation management: Retrieve details about your Instagram DM conversations, including participants and recent messages, to help you stay connected.
  • Profile and media access: Instantly fetch your profile details, statistics, and all media you've posted—photos, videos, and reels—so your agent can reference or repurpose your content.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Instagram account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

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.
3

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 Instagram via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

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 Instagram connections to use
5

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 Instagram session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["instagram"]
    )
    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 Instagram tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

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
7

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 Instagram assistant agent with MCP tools
    agent = AssistantAgent(
        name="instagram_assistant",
        description="An AI assistant that helps with Instagram 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 Instagram tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Instagram 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 Instagram 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 Instagram 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 Instagram session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["instagram"]
    )
    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 Instagram assistant agent with MCP tools
        agent = AssistantAgent(
            name="instagram_assistant",
            description="An AI assistant that helps with Instagram 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 Instagram 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 Instagram 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 Instagram, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Instagram action and event your agent gets out of the box.

Create Carousel Container

Create a draft carousel post with multiple images/videos before publishing.

Delete Comment

Tool to delete a comment on Instagram media.

Delete Messenger Profile

Tool to delete messenger profile settings for an Instagram account.

Get Conversation

Get details about a specific Instagram DM conversation (participants, etc).

Get IG Comment Replies

Get replies to a specific Instagram comment.

Get Instagram Media

Get a published Instagram Media object (photo, video, story, reel, or carousel).

Get IG Media Children

Tool to get media objects (images/videos) that are children of an Instagram carousel/album post.

Get IG Media Comments

Tool to retrieve comments on an Instagram media object.

Get IG Media Insights

Tool to get insights and metrics for Instagram media objects (photos, videos, reels, carousel albums).

Get IG User Content Publishing Limit

Get an Instagram Business Account's current content publishing usage.

Get IG User Live Media

Get live media objects during an active Instagram broadcast.

Get IG User Media

Get Instagram user's media collection (posts, photos, videos, reels, carousels).

Get IG User Stories

Get active story media objects for an Instagram Business or Creator account.

Get IG User Tags

Get Instagram media where the user has been tagged by other users.

Get Messenger Profile

Get the messenger profile settings for an Instagram account.

Get Page Conversations

Get Instagram conversations for a Page connected to an Instagram Business account.

Get User Info

Get Instagram Business Account info including profile details and statistics.

Get User Insights

Get Instagram account-level insights and analytics (profile views, reach, follower count, etc.

List All Conversations

List all Instagram DM conversations for the authenticated user.

List All Messages

List all messages from a specific Instagram DM conversation.

Mark Seen

Mark Instagram DM messages as read/seen for a specific user.

Post IG Comment Replies

Tool to create a reply to an Instagram comment.

Post IG Media Comments

Tool to create a comment on an Instagram media object.

Post IG User Media

Tool to create a media container for Instagram posts.

Publish IG User Media

Tool to publish a media container to an Instagram Business account.

Reply to IG User Mentions

Tool to reply to a mention of your Instagram Business or Creator account.

Send Image

Send an image via Instagram DM to a specific user.

Send Text Message

Send a text message to an Instagram user via DM in an existing conversation.

Update Messenger Profile

Tool to update the messenger profile settings for an Instagram account.

FAQ

Frequently asked questions

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

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 Instagram tools.

Yes, absolutely. You can configure which Instagram 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.

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 Instagram data and credentials are handled as safely as possible.

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