How to integrate Swaggerhub MCP with Pydantic AI

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Introduction

This guide walks you through connecting Swaggerhub to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Swaggerhub
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Swaggerhub workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Swaggerhub
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Swaggerhub
  • MCPServerStreamableHTTP connects to the Swaggerhub MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Swaggerhub
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["swaggerhub"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Swaggerhub tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
swaggerhub_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[swaggerhub_mcp],
    instructions=(
        "You are a Swaggerhub assistant. Use Swaggerhub tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Swaggerhub endpoint
  • The agent uses GPT-5 to interpret user commands and perform Swaggerhub operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Swaggerhub.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Swaggerhub API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Swaggerhub and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Swaggerhub
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["swaggerhub"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    swaggerhub_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[swaggerhub_mcp],
        instructions=(
            "You are a Swaggerhub assistant. Use Swaggerhub tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Swaggerhub.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Swaggerhub through Composio's Tool Router. With this setup, your agent can perform real Swaggerhub actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Swaggerhub for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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 Pydantic AI?

Yes, you can. Pydantic AI 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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