How to integrate OneSimpleAPI MCP with Pydantic AI

This guide walks you through connecting OneSimpleAPI to Pydantic AI using the Composio tool router. By the end, you'll have a working OneSimpleAPI agent that can create qr codes, generate pdfs, capture screenshots, convert currencies, and create short urls through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a OneSimpleAPI account through Composio's OneSimpleAPI MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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OneSimpleAPI is a utility API platform for web content, images, PDFs, QR codes, URL tools, validation, exchange rates, and file management. It gives developers one simple API key for many common backend tasks.

15 Tools

Introduction

This guide walks you through connecting OneSimpleAPI to Pydantic AI using the Composio tool router. By the end, you'll have a working OneSimpleAPI agent that can create qr codes, generate pdfs, capture screenshots, convert currencies, and create short urls through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a OneSimpleAPI account through Composio's OneSimpleAPI MCP server.

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

Also integrate OneSimpleAPI with

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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 OneSimpleAPI
  • 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 OneSimpleAPI 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 OneSimpleAPI MCP server, and what's possible with it?

The OneSimpleAPI MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OneSimpleAPI account. It provides structured and secure access to web, image, document, URL, validation, currency, and file utilities, so your agent can capture webpages, transform images, generate PDFs and QR codes, manage short links, and validate content on your behalf.

  • Web captures and PDF creation: Have your agent capture screenshots of webpages or raw HTML, or turn that content into hosted PDF files.
  • Image inspection and transformation: Let the agent inspect image dimensions and metadata, then resize, crop, rotate, flip, filter, add borders, or optimize images.
  • QR codes and short links: Direct your agent to generate hosted QR codes, create configurable short links, expand shortened links, and review link click statistics.
  • Content and data checks: Instruct your agent to analyze text readability and sentiment, validate email addresses, convert colors, and inspect image details.
  • Currency, pricing, and file management: Have your agent convert currencies, calculate localized pricing discounts, list generated files, and delete files you no longer need.

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 step09 STEPS
1

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
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like OneSimpleAPI
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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
5

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 OneSimpleAPI
  • MCPServerStreamableHTTP connects to the OneSimpleAPI MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 OneSimpleAPI
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["onesimpleapi"],
    )
    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 OneSimpleAPI 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
onesimpleapi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[onesimpleapi_mcp],
    instructions=(
        "You are a OneSimpleAPI assistant. Use OneSimpleAPI tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the OneSimpleAPI endpoint
  • The agent uses GPT-5 to interpret user commands and perform OneSimpleAPI operations
  • The instructions field defines the agent's role and behavior
8

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 OneSimpleAPI.\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
  • OneSimpleAPI API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 OneSimpleAPI 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 OneSimpleAPI
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["onesimpleapi"],
    )
    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
    onesimpleapi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[onesimpleapi_mcp],
        instructions=(
            "You are a OneSimpleAPI assistant. Use OneSimpleAPI 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 OneSimpleAPI.\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 OneSimpleAPI through Composio's Tool Router. With this setup, your agent can perform real OneSimpleAPI 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 + OneSimpleAPI for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Analyze Readability

Analyze text for readability, grade level, reading time, difficult-word counts, and sentiment.

Calculate PPP Discount

Calculate a purchasing-power-parity discount and localized price between an origin and a destination country.

Capture Screenshot

Capture a webpage URL or raw HTML as a hosted screenshot and return its URL and rendering metadata.

Convert Currency

Convert an amount between supported currencies and return the converted value and exchange rate.

Create Short URL

Create a OneSimpleAPI short URL with optional one-time-use, redirect, query-forwarding, and active-date controls.

Delete File

Delete a generated OneSimpleAPI file by its hosted URL and return the updated file record.

Expand Short URL

Resolve a shortened URL and return its final URL, redirect count, and redirect trace.

Generate or Convert Color

Generate a deterministic color palette from text or convert a supplied color into HEX, RGB, HSL, and related palette values.

Generate PDF

Generate a PDF from either a webpage URL or raw HTML and return the hosted PDF URL and page metadata.

Generate QR Code

Generate a hosted PNG or SVG QR code for a message and return its URL.

Get Image Information

Extract dimensions, image metadata, EXIF camera fields, and available GPS details from an image URL.

List Files

Return one page of generated files owned by the connected account, optionally filtered by live or deleted status.

List Short URLs

Return one page of OneSimpleAPI short URLs and their click statistics.

Transform Image

Resize, crop, rotate, flip, filter, border, optimize, and host an image, returning the generated image URL and metadata.

Validate Email

Validate an email address and assess its domain, MX records, deliverability, disposability, role status, and registration safety.

FRAMEWORKS

How to build OneSimpleAPI MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use OneSimpleAPI MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use OneSimpleAPI MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use OneSimpleAPI MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use OneSimpleAPI MCP with Claude Cowork

Codex logo

Codex

Use OneSimpleAPI MCP with Codex

OpenClaw logo

OpenClaw

Use OneSimpleAPI MCP with OpenClaw

Hermes logo

Hermes

Use OneSimpleAPI MCP with Hermes

CLI logo

CLI

Use OneSimpleAPI MCP with CLI

Google ADK logo

Google ADK

Use OneSimpleAPI MCP with Google ADK

LangChain logo

LangChain

Use OneSimpleAPI MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use OneSimpleAPI MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use OneSimpleAPI MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use OneSimpleAPI MCP with LlamaIndex

CrewAI logo

CrewAI

Use OneSimpleAPI MCP with CrewAI

FAQ

Frequently asked questions

With a standalone OneSimpleAPI MCP server, the agents and LLMs can only access a fixed set of OneSimpleAPI tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from OneSimpleAPI and many other apps based on the task at hand, all through a single MCP endpoint.

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 OneSimpleAPI tools.

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

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