How to integrate Postalytics MCP with Autogen

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Introduction

This guide walks you through connecting Postalytics to AutoGen using the Composio tool router. By the end, you'll have a working Postalytics agent that can create a new direct mail campaign, sync contacts from hubspot to postalytics, track delivery status for recent campaigns through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Postalytics account through Composio's Postalytics 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 Postalytics
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Postalytics tools
  • Run a live chat loop where you ask the agent to perform Postalytics 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 Postalytics MCP server, and what's possible with it?

The Postalytics MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Postalytics account. It provides structured and secure access so your agent can perform Postalytics operations on your behalf.

Supported Tools & Triggers

Tools
Add AccountTool to create a new sub-account in the Postalytics system.
Add ContactTool to add a contact to a specified contact list with their information.
Create New CampaignTool to create a new direct mail campaign in Postalytics.
Create Suppression ListTool to create a new suppression list that can be used in campaigns to suppress contacts from being sent mail.
Create Suppression List ContactTool to create a new suppression contact on a specified suppression list.
Create TemplateTool to create a new template with full HTML for postcard or letter.
Create WebhookTool to create a new webhook to receive campaign event notifications from Postalytics.
Delete AccountTool to delete a Postalytics account and all associated campaigns, templates, and lists.
Delete CampaignTool to delete a campaign from the system.
Delete Suppression ListTool to delete a specified suppression list.
Delete Suppression List ContactTool to delete a specific contact from a suppression list.
Get All Contact ListsTool to retrieve all contact lists for an account.
Get All Contacts on a ListTool to retrieve all contacts from a specified contact list with pagination support.
Get All Drip CampaignsTool to retrieve all triggered drip campaign names and endpoint IDs in the account.
Get All FlowsTool to retrieve all flows for the requester's account.
Get All WebhooksTool to retrieve all webhooks configured for the authenticated account.
Get IntegrationsTool to retrieve all Connect integrations configured for the authenticated user's account.
Get My AccountTool to retrieve basic account information for the authenticated user.
Get Suppression ListTool to get the details of a suppression list based on the id supplied.
Get Suppression List ContactTool to retrieve a specific contact from a suppression list.
Get Suppression List ContactsTool to get all contacts on a specified suppression list.
Get Suppression ListsTool to retrieve all suppression lists for the authenticated user.
Update AccountTool to update an existing account in the Postalytics system.
Update Suppression List ContactTool to update a suppression contact on the specified suppression list.

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 Postalytics 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 Postalytics 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 Postalytics 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 Postalytics session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["postalytics"]
    )
    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 Postalytics 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 Postalytics assistant agent with MCP tools
    agent = AssistantAgent(
        name="postalytics_assistant",
        description="An AI assistant that helps with Postalytics 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 Postalytics 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 Postalytics 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 Postalytics 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 Postalytics 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 Postalytics session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["postalytics"]
    )
    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 Postalytics assistant agent with MCP tools
        agent = AssistantAgent(
            name="postalytics_assistant",
            description="An AI assistant that helps with Postalytics 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 Postalytics 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 Postalytics 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 Postalytics, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Postalytics MCP Agent with another framework

OpenAI Agents SDK

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Claude Agent SDK

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Use Postalytics MCP with Claude Agent SDK

Google ADK

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Use Postalytics MCP with Google ADK

LangChain

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Use Postalytics MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Postalytics MCP with Vercel AI SDK

Mastra AI

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Use Postalytics MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Postalytics MCP with LlamaIndex

CrewAI

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Use Postalytics MCP with CrewAI

Claude Code

Claude Code

Use Postalytics MCP with Claude Code

Codex

Codex

Use Postalytics MCP with Codex

FAQ

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

With a standalone Postalytics MCP server, the agents and LLMs can only access a fixed set of Postalytics tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Postalytics 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 Postalytics tools.

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

Yes, absolutely. You can configure which Postalytics 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 Postalytics data and credentials are handled as safely as possible.

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