How to integrate Confluence MCP with Autogen

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Introduction

This guide walks you through connecting Confluence to AutoGen using the Composio tool router. By the end, you'll have a working Confluence agent that can create a project documentation page in marketing space, add 'urgent' label to q3 planning page, publish team meeting summary as a blog post, create a private space for product roadmap drafts through natural language commands.

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

The Confluence MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Confluence account. It provides structured and secure access to your Confluence spaces, pages, and content, so your agent can perform actions like creating pages, publishing blog posts, organizing spaces, and managing metadata on your behalf.

  • Automated page and space creation: Instantly create new Confluence pages or entire spaces, empowering your agent to generate project documentation, wikis, or knowledge bases as needed.
  • Effortless blog post publishing: Let your agent draft and publish new blog posts within specified Confluence spaces to keep your team up-to-date and share knowledge seamlessly.
  • Content labeling and metadata management: Have your agent add labels and custom properties to pages, blog posts, or spaces, making it easy to organize, tag, and categorize information for better discoverability.
  • Private space setup and management: Direct your agent to create private, isolated workspaces for sensitive projects or teams, ensuring only authorized collaborators have access.
  • Custom content property automation: Empower your agent to attach or update custom metadata on pages, blog posts, spaces, or whiteboards, streamlining your internal documentation workflows.

Supported Tools & Triggers

Tools
Add Content LabelTool to add labels to a piece of content.
Get Space by IDTool to retrieve a confluence space by its id.
Create BlogpostTool to create a new confluence blog post.
Create Blogpost PropertyTool to create a property on a specified blog post.
Create Whiteboard PropertyTool to create a new content property on a whiteboard.
Create PageTool to create a new confluence page in a specified space.
Create Page PropertyTool to create a property on a confluence page.
Create Private SpaceTool to create a private confluence space.
Create SpaceTool to create a new confluence space.
Create Space PropertyTool to create a new property on a confluence space.
Create WhiteboardTool to create a new confluence whiteboard.
Delete Blogpost PropertyTool to delete a blog post property.
Delete Page Content PropertyTool to delete a content property from a page by property id.
Delete Whiteboard Content PropertyTool to delete a content property from a whiteboard by property id.
Delete PageTool to delete a confluence page.
Delete SpaceTool to delete a confluence space by its key.
Delete Space PropertyTool to delete a space property.
Get Attachment LabelsTool to list labels on an attachment.
Get AttachmentsTool to retrieve attachments of a confluence page.
Get Audit LogsTool to retrieve confluence audit records.
Get Blogpost by IDTool to retrieve a specific confluence blog post by its id.
Get Blogpost LabelsTool to retrieve labels of a specific confluence blog post by id.
Get Blogpost Like CountTool to get like count for a confluence blog post.
Get Blogpost OperationsTool to retrieve permitted operations for a confluence blog post.
Get BlogpostsTool to retrieve a list of blog posts.
Get Blog PostsTool to retrieve a list of blog posts.
Get Blog Posts For LabelTool to list all blog posts under a specific label.
Get Blogpost Version DetailsTool to retrieve details for a specific version of a blog post.
Get Blogpost VersionsTool to retrieve all versions of a specific blog post.
Get Child PagesTool to list all direct child pages of a given confluence page.
Get Blog Post Content PropertiesTool to retrieve all content properties on a blog post.
Get Page Content PropertiesTool to retrieve all content properties on a page.
Get Content RestrictionsTool to retrieve restrictions on a confluence content item.
Get Current UserTool to get information about the currently authenticated user.
Get Inline Comments for Blog PostTool to retrieve inline comments for a confluence blog post.
Get LabelsTool to retrieve all labels in a confluence site.
Get Page LabelsTool to retrieve labels of a specific confluence page by id.
Get Labels for SpaceTool to list labels on a space.
Get Labels for Space ContentTool to list labels on all content in a space.
Get Page AncestorsTool to retrieve all ancestors for a given confluence page by its id.
Get Page by IDTool to retrieve a confluence page by its id.
Get Page Like CountTool to get like count for a confluence page.
Get PagesTool to retrieve a list of pages.
Get Page VersionsTool to retrieve all versions of a specific confluence page.
Get Space by IDTool to retrieve a confluence space by its id.
Get Space ContentsTool to retrieve content in a confluence space.
Get Space PropertiesTool to get properties of a confluence space.
Get SpacesTool to retrieve a list of confluence spaces.
Get Anonymous UserTool to retrieve information about the anonymous user.
Search ContentSearches for content by filtering pages from the confluence v2 api with intelligent ranking.
Search UsersSearches for users using user-specific queries from the confluence query language (cql).
Update BlogpostTool to update a confluence blog post's title or content.
Update Blogpost PropertyTool to update a property of a specified blog post.
Update Page Content PropertyTool to update a content property on a confluence page.
Update Whiteboard Content PropertyTool to update a content property on a whiteboard.
Update PageTool to update an existing confluence page.
Update Space PropertyTool to update a space property.

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

How to build Confluence MCP Agent with another framework

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LangChain

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Vercel AI SDK

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Mastra AI

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LlamaIndex

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Use Confluence MCP with LlamaIndex

CrewAI

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Use Confluence MCP with CrewAI

Claude Code

Claude Code

Use Confluence MCP with Claude Code

FAQ

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

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

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

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

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