How to integrate Agility cms MCP with Autogen

This guide walks you through connecting Agility cms to AutoGen using the Composio tool router. By the end, you'll have a working Agility cms agent that can list all authors for our blog, fetch content items tagged 'product-launch', show sitemap paths for the main website through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Agility cms account through Composio's Agility cms MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease.

9 Tools

Introduction

This guide walks you through connecting Agility cms to AutoGen using the Composio tool router. By the end, you'll have a working Agility cms agent that can list all authors for our blog, fetch content items tagged 'product-launch', show sitemap paths for the main website through natural language commands.

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

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

Also integrate Agility cms with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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

The Agility cms MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Agility CMS account. It provides structured and secure access to your content models, pages, authors, categories, and more, so your agent can fetch content, retrieve metadata, manage sitemaps, and automate content discovery on your behalf.

  • Content item and list retrieval: Instantly fetch specific content items by ID or pull paginated lists by reference name, complete with filtering and sorting.
  • Dynamic schema and model insights: Allow your agent to get details on content models and page modules, so it can adapt to schema changes and build flexible digital experiences.
  • Page and sitemap management: Retrieve detailed information about pages—including metadata, content zones, and components—or pull the flat sitemap for custom routing and navigation logic.
  • Author, category, and tag lookup: Effortlessly list all authors, categories, and tags within your CMS instance to enable rich content filtering and assignment workflows.
  • Log and sync monitoring: Access recent sync logs to keep tabs on content updates and ensure your agent is always working with the latest data.

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

Supported Tools

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

Get API Types

Tool to retrieve all enum types used throughout the Agility CMS Management API.

Get Content Item

Tool to fetch details of a content item by Content ID.

Get Content List

Retrieves a paginated list of content items by reference name from Agility CMS.

Get Content Models

Tool to retrieve content models and page modules.

Get Logs

Retrieve sync items (content change logs) from Agility CMS using the Content Sync API.

Get Page

Tool to retrieve details of a Page, including metadata, content zones, and components.

Get Page Modules

Retrieves page module definitions from Agility CMS.

Get Sitemap Flat

Retrieves the flat sitemap for a specific channel and locale in Agility CMS.

Sync Pages

Retrieves all page items from Agility CMS in paged format with sync tokens for incremental updates.

FRAMEWORKS

How to build Agility cms MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Agility cms MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Agility cms MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Agility cms MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Agility cms MCP with Claude Cowork

Codex logo

Codex

Use Agility cms MCP with Codex

OpenClaw logo

OpenClaw

Use Agility cms MCP with OpenClaw

Hermes logo

Hermes

Use Agility cms MCP with Hermes

CLI logo

CLI

Use Agility cms MCP with CLI

Google ADK logo

Google ADK

Use Agility cms MCP with Google ADK

LangChain logo

LangChain

Use Agility cms MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Agility cms MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Agility cms MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Agility cms MCP with LlamaIndex

CrewAI logo

CrewAI

Use Agility cms MCP with CrewAI

FAQ

Frequently asked questions

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

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

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