How to integrate Quaderno MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Quaderno to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Quaderno agent that can calculate tax rate for a u.s. sale, create an invoice for a new customer, email finalized invoice to a client, add a new product with custom tax through natural language commands.

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

The Quaderno MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Quaderno account. It provides structured and secure access to your tax automation, invoicing, and compliance workflows, so your agent can calculate taxes, generate invoices, manage contacts and products, and handle essential document delivery on your behalf.

  • Automated tax rate calculation: Ask your agent to instantly determine the correct tax rate for any address or transaction type before creating invoices or processing sales.
  • Invoice creation and delivery: Let your agent generate detailed invoices for customers and deliver them directly via email, ensuring seamless billing operations.
  • Contact and product management: Easily create new customer or vendor contacts, add new products, or permanently delete outdated items from your Quaderno account—all through your agent.
  • Expense and tax ID cleanup: Direct your agent to remove specific expenses or registered tax IDs when they're no longer needed, keeping your records tidy and up to date.
  • Credit note and coupon handling: Your agent can deliver finalized credit notes to customers and permanently delete coupons as part of your accounting and revenue operations.

Supported Tools & Triggers

Tools
Calculate Tax RateTool to calculate applicable tax rate for given address and transaction type.
Create ContactTool to create a new contact (customer or vendor).
Create InvoiceTool to create a new invoice.
Create ProductTool to create a new product.
Delete CouponTool to permanently delete a coupon.
Delete ExpenseTool to permanently delete an expense by id.
Delete ProductTool to permanently delete a product by id.
Delete Tax IDTool to permanently delete a registered tax id by id.
Deliver Credit NoteTool to deliver a credit note to the customer via email.
Deliver InvoiceTool to deliver an invoice to the customer via email.
List ContactsTool to list contacts, paginated and filterable by name, email, or tax id.
List CouponsTool to list all coupons.
List EvidenceTool to list all evidence objects.
List ExpensesTool to list all expenses, paginated.
List Tax JurisdictionsTool to list all tax jurisdictions.
List ProductsTool to list all products.
List Registered Tax IDsTool to list all registered tax ids.
List Reporting RequestsTool to list all reporting requests.
List SessionsTool to list all quaderno checkout sessions, paginated and filterable by status.
List Tax CodesTool to list all supported tax codes.
List WebhooksTool to list all webhooks.
Retrieve ContactTool to retrieve details of an existing contact by id.
Retrieve CouponTool to retrieve details of an existing coupon by id.
Retrieve EvidenceTool to retrieve details of an existing evidence object by id.
Retrieve InvoiceTool to retrieve details of an existing invoice by id.
Retrieve Tax JurisdictionTool to retrieve a tax jurisdiction by id.
Retrieve ProductTool to retrieve details of an existing product by id.
Update Credit NoteTool to update a credit note.
Update InvoiceTool to update an invoice.
Update productTool to update a product; unspecified fields remain unchanged.
Validate Tax IDTool to validate a tax id.
Void Credit NoteTool to void a credit note.

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 Quaderno 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 Quaderno.

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 Quaderno Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["quaderno"]
)

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

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 Quaderno MCP Agent with another framework

FAQ

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

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

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

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

Used by agents from

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

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