How to integrate Swaggerhub MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Swaggerhub to the OpenAI Agents SDK 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 OpenAI Agents SDK 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 necessary dependencies
  • Initialize Composio and create a Tool Router session for Swaggerhub
  • Configure an AI agent that can use Swaggerhub as a tool
  • Run a live chat session where you can ask the agent to perform Swaggerhub operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Swaggerhub project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Swaggerhub.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Swaggerhub Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["swaggerhub"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only swaggerhub.
  • The router checks the user's Swaggerhub connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Swaggerhub.
  • This approach keeps things lightweight and lets the agent request Swaggerhub tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Swaggerhub. "
        "Help users perform Swaggerhub operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Swaggerhub and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Swaggerhub operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Swaggerhub.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Swaggerhub and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["swaggerhub"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Swaggerhub. "
        "Help users perform Swaggerhub operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Swaggerhub MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Swaggerhub.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

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