How to integrate Api2pdf MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Api2pdf to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Api2pdf agent that can merge monthly invoices into one pdf, extract specific pages from a large pdf, add custom header and footer to document, convert pdf report to html for web use through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Api2pdf account through Composio's Api2pdf 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 Api2pdf
  • Configure an AI agent that can use Api2pdf as a tool
  • Run a live chat session where you can ask the agent to perform Api2pdf 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 Api2pdf MCP server, and what's possible with it?

The Api2pdf MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Api2pdf account. It provides structured and secure access to powerful PDF generation and manipulation features, so your agent can generate PDFs from HTML or URLs, merge or optimize documents, extract or reorder pages, and more—automatically and on your behalf.

  • PDF generation from web content: Instruct your agent to convert HTML or URLs into high-quality PDFs using engines like wkhtmltopdf or Headless Chrome.
  • Merge and optimize PDFs: Have your agent combine multiple PDFs into a single file or optimize existing documents to reduce file size without sacrificing quality.
  • Advanced PDF manipulation: Direct your agent to extract specific pages, reorder existing pages, or add custom headers and footers for consistent branding or page numbering.
  • Barcode and QR code generation: Let your agent instantly create barcode or QR code images from any text value, ready to embed in documents or use elsewhere.
  • Document conversion and preview: Ask your agent to convert PDFs to HTML with LibreOffice or generate thumbnail previews for quick visual reference.

Supported Tools & Triggers

Tools
Add Header FooterTool to add headers and footers to a pdf document.
Delete PDFTool to delete a previously generated pdf.
Extract PDF PagesTool to extract specific pages from a pdf document.
LibreOffice PDF to HTMLTool to convert a pdf document to html using libreoffice.
LibreOffice ThumbnailTool to generate a thumbnail image of a document using libreoffice.
Merge PDFsTool to merge multiple pdf documents into a single pdf.
Optimize PDFTool to optimize a pdf document to reduce file size while maintaining quality.
Reorder PDF PagesTool to reorder pages of a pdf document.
Generate Barcode or QR CodeTool to generate barcodes or qr codes using zebra crossing (zxing).

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 Api2pdf 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 Api2pdf.

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 Api2pdf Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["api2pdf"]
)

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 api2pdf.
  • The router checks the user's Api2pdf connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Api2pdf.
  • This approach keeps things lightweight and lets the agent request Api2pdf 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 Api2pdf. "
        "Help users perform Api2pdf 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 Api2pdf 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 Api2pdf 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 Api2pdf.
  • 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 Api2pdf 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=["api2pdf"]
)
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 Api2pdf. "
        "Help users perform Api2pdf 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 Api2pdf MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Api2pdf.

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.

How to build Api2pdf MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Api2pdf MCP with Claude Agent SDK

Google ADK

Google ADK

Use Api2pdf MCP with Google ADK

LangChain

LangChain

Use Api2pdf MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Api2pdf MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Api2pdf MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Api2pdf MCP with LlamaIndex

CrewAI

CrewAI

Use Api2pdf MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Api2pdf MCP?

With a standalone Api2pdf MCP server, the agents and LLMs can only access a fixed set of Api2pdf tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Api2pdf 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 Api2pdf tools.

Can I manage the permissions and scopes for Api2pdf while using Tool Router?

Yes, absolutely. You can configure which Api2pdf 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 Api2pdf data and credentials are handled as safely as possible.

Used by agents from

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

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