How to integrate Swaggerhub MCP with Autogen

GET STARTED FOR FREE
Framework Integration Gradient
Swaggerhub Logo
AutoGen Logo
divider

Introduction

This guide walks you through connecting Swaggerhub to AutoGen using the Composio tool router. By the end, you'll have a working Swaggerhub agent that can list all apis i have access to, create a new api named petstore, update the description for my orders api through natural language commands.

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

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

Supported Tools & Triggers

Tools
Add Access Control for TeamsTool to assign access control roles to teams on a SwaggerHub resource.
Add Access Control for UsersTool to assign access control roles to users on a SwaggerHub resource.
Delete Table of Contents EntryTool to delete a table of contents entry from SwaggerHub portal.
Get Access Control UsersTool to retrieve the list of users assigned access control on a SwaggerHub resource.
Get API Default VersionTool to get the default version identifier of a SwaggerHub API.
Get API VersionsTool to retrieve a list of API versions for a specific API in SwaggerHub.
Get Consumer ProductsTool to get a list of products that are visible to the consumer in a SwaggerHub portal.
Get API DefinitionTool to get the OpenAPI definition of a specified API version from SwaggerHub.
Get Domain Default VersionTool to retrieve the default version identifier of a SwaggerHub domain.
Get domain definitionTool to retrieve the OpenAPI definition of a specified domain version from SwaggerHub.
Get Domain JSON DefinitionTool to retrieve the OpenAPI definition for a specified domain version in JSON format.
Get Domain Lifecycle SettingsTool to get the published status for a specific domain and version in SwaggerHub.
Get Domain Private SettingsTool to retrieve the visibility (public or private) of a domain version in SwaggerHub.
Get Domain VersionsTool to get a list of domain versions from SwaggerHub.
Get Domain YAML DefinitionTool to retrieve the OpenAPI definition for a specified domain version in YAML format from SwaggerHub.
Get JSON API DefinitionTool to download OpenAPI definition as a JSON file from SwaggerHub Portal API.
Get JSON DefinitionTool to get the OpenAPI definition for a specified API version in JSON format.
Get lifecycle settingsTool to get the published status for the specified API and version.
Get Organization MembersTool to retrieve a list of organization members and their roles from SwaggerHub.
Get User OrganizationsTool to get organizations for a user.
Get Organization Projects V2Tool to get all projects of an organization in SwaggerHub.
Get Owner APIsTool to get a list of APIs for a specified owner in SwaggerHub.
Get owner domainsTool to retrieve domains owned by a specific SwaggerHub user or organization.
Get PortalTool to retrieve information about a portal.
Get Portal Access RequestsTool to retrieve access requests for a portal in SwaggerHub.
Get Portal AttachmentTool to get informational attachment metadata from SwaggerHub Portal.
Get Portal ProductTool to retrieve detailed information about a specific product resource.
Get Portal ProductsTool to get products for a specific portal that match your criteria.
Get PortalsTool to search for available portals.
Get Portal TemplatesTool to get templates for a specific portal that match your criteria.
Get API Version Private SettingsTool to get the visibility (public or private) of an API version.
List Resource Types and RolesTool to list available resource types and assignable roles for each in a SwaggerHub organization.
Get TemplatesTool to retrieve a list of templates for an owner in SwaggerHub.
Get User RolesTool to retrieve all roles assigned to a user across organization resources in SwaggerHub.
Get YAML API DefinitionTool to download OpenAPI definition as a YAML file from SwaggerHub Portal API.
Get YAML DefinitionTool to get the OpenAPI definition in YAML format for the specified API version from SwaggerHub.
List AttachmentsTool to retrieve all attachments for a portal or product.
Remove Access Control for TeamsTool to remove access control for teams from a SwaggerHub resource.
Remove Access Control For UsersTool to remove access control for users from a SwaggerHub organizational resource.
Remove Organization MembersTool to remove members from a SwaggerHub organization.
Search APIsTool to search SwaggerHub APIs.
Search APIs and DomainsTool to search SwaggerHub APIs, domains, and templates.
Search DomainsTool to search SwaggerHub domains.
Search Published PortalTool to search published portal content.
Update Access Control for TeamsTool to update access control roles for teams on a SwaggerHub resource.
Update Access Control for UsersTool to update access control roles for users on a SwaggerHub resource.
Update Access Control for TeamsTool to update access control for teams on a SwaggerHub resource.
Update Access Control UsersTool to update access control roles for users on a SwaggerHub resource.
Update PortalTool to update specific portal information in SwaggerHub.

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

How to build Swaggerhub MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Swaggerhub MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Swaggerhub MCP with Claude Agent SDK

Google ADK

Google ADK

Use Swaggerhub MCP with Google ADK

LangChain

LangChain

Use Swaggerhub MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Swaggerhub MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Swaggerhub MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Swaggerhub MCP with LlamaIndex

CrewAI

CrewAI

Use Swaggerhub MCP with CrewAI

Claude Code

Claude Code

Use Swaggerhub MCP with Claude Code

Codex

Codex

Use Swaggerhub MCP with Codex

FAQ

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

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

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free