How to integrate ActiveMerge MCP with Autogen

This guide walks you through connecting ActiveMerge to AutoGen using the Composio tool router. By the end, you'll have a working ActiveMerge agent that can generate invoices from saved templates, merge contract files for client signature, store signed ndas in project folders through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a ActiveMerge account through Composio's ActiveMerge MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

ActiveMerge logoActiveMerge
Api Key

ActiveMerge is a document automation platform for generating documents, images, merged files, and e-signature workflows. It helps teams turn templates and stored files into finished, shareable documents faster.

13 Tools

Introduction

This guide walks you through connecting ActiveMerge to AutoGen using the Composio tool router. By the end, you'll have a working ActiveMerge agent that can generate invoices from saved templates, merge contract files for client signature, store signed ndas in project folders through natural language commands.

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

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

Also integrate ActiveMerge with

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

The ActiveMerge MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ActiveMerge account. It provides structured and secure access to your templates, workflows, generation jobs, credits, and stored files, so your agent can generate documents, create images, run template workflows, track generation progress, and manage generated files on your behalf.

  • Template-based document generation: Have your agent review available document templates and their required placeholders, then generate documents using your case-sensitive data.
  • Automated image creation: Let the agent inspect image templates, create images from your records, and check each generation job for progress, errors, and completed output.
  • Multi-document workflows: Direct your agent to find available workflows, collect their required placeholders, and generate documents for every template in a chosen workflow.
  • Generation tracking and credit checks: Instruct your agent to check remaining credits before starting work, then review document generation history and job status.
  • Generated file management: Have your agent browse stored files, save completed document outputs to permanent storage, and prepare stored files for download.

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

Supported Tools

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

Generate Document

Start asynchronous document generation from a template and case-sensitive placeholder data.

Generate Images

Start an asynchronous image-generation job from inline JSON records.

Generate Workflow Documents

Generate documents for every template in an ActiveMerge workflow using case-sensitive placeholder data.

Get Credits

Get total, used, remaining, plan, and prepaid ActiveMerge credits before running credit-consuming generation tools.

Get Document Generations

Get one document-generation job by ID, or list and filter generation history when no job ID is supplied.

Get Document Template Placeholders

Return the case-sensitive placeholder names required by one document template.

Get File Download URL

Create a temporary download URL for a file in ActiveMerge cloud storage.

Get Image Generation

Get an image-generation job's progress, credit usage, errors, and temporary ZIP download URL when complete.

Get Image Templates

List image templates and basic placeholders, or get complete dimensions, positions, defaults, and styles for one template when template_id is supplied.

Get Workflows

List available ActiveMerge workflows, or return the case-sensitive placeholders for one workflow when workflow_id is supplied.

List Document Templates

List document templates available to the connected ActiveMerge account, including the unique template IDs needed for placeholder lookup and generation.

List Stored Files

List the immediate files and folders at the ActiveMerge cloud-storage root, or directly inside parent_folder_id when supplied.

Save Generated Files

Save non-expired output from a completed document-generation job to permanent ActiveMerge cloud storage.

FAQ

Frequently asked questions

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

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

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