How to integrate Quaderno MCP with LlamaIndex

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Introduction

This guide walks you through connecting Quaderno to LlamaIndex 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 through natural language commands.

This guide will help you understand how to give your LlamaIndex 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.

Also integrate Quaderno with

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Quaderno
  • Connect LlamaIndex to the Quaderno MCP server
  • Build a Quaderno-powered agent using LlamaIndex
  • Interact with Quaderno through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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Contact and product management: Easily create new customer or vendor contacts, add new products, or permanently delete outdated items from your Quaderno account—all through your agent.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
Add Expense PaymentAdds a payment to an existing expense in Quaderno.
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 CouponTool to create a new discount coupon in Quaderno.
Create EstimateCreates a new estimate/quote in Quaderno for a customer with line items.
Create EvidenceTool to create a new location evidence for tax compliance.
Create ExpenseTool to create a business expense in Quaderno.
Create InvoiceCreates a new invoice in Quaderno for a customer with line items.
Create ProductCreates a new product that can be used as a line item in invoices, credit notes, and expenses.
Create ReceiptCreates a new receipt in Quaderno documenting payment for goods or services.
Create RecurringTool to create a recurring document in Quaderno that automatically generates invoices on a schedule.
Create Report RequestTool to request a new report generation in Quaderno.
Create Tax IDTool to create a tax ID in a specific jurisdiction.
Create TransactionTool to create a sale or refund transaction in Quaderno.
Create WebhookTool to create a new webhook in Quaderno to receive event notifications.
Delete ContactTool to permanently delete a contact by ID.
Delete CouponTool to permanently delete a coupon.
Delete EstimatePermanently deletes an estimate from Quaderno by its ID.
Delete ExpensePermanently deletes an expense from Quaderno by its ID.
Delete ProductTool to permanently delete a product by ID.
Delete RecurringTool to permanently delete a recurring by ID.
Delete Tax IDPermanently deletes a registered tax ID from your Quaderno account.
Delete WebhookTool to permanently delete a webhook by ID.
Deliver Credit NoteSends a credit note to the customer via email.
Deliver EstimateDelivers an estimate to the customer via email.
Deliver InvoiceDelivers an invoice to the customer via email.
Deliver ReceiptSends a receipt to the customer via email.
Get AuthorizationTool to retrieve account credentials and verify API access.
Get EstimateTool to retrieve the details of an existing estimate by ID.
List ContactsTool to list contacts, paginated and filterable by name, email, or tax ID.
List CouponsTool to list all coupons.
List CreditsTool to list all credit notes from Quaderno.
List EstimatesTool to list all estimates in the account, paginated and sorted by creation date (newest first).
List EvidenceTool to list all evidence objects.
List ExpensesList all expenses from Quaderno with pagination support.
List InvoicesTool to list all invoices from Quaderno with filtering support.
List Tax JurisdictionsTool to list all tax jurisdictions.
List ProductsList all products (goods and services) from your Quaderno account.
List ReceiptsTool to list all receipts from Quaderno with optional filtering by search query, date range, payment state, processor ID, or customer ID.
List RecurringsList all recurring documents (invoices, expenses, or estimates) from your Quaderno account.
List Registered Tax IDsTool to list all registered tax IDs.
List Reporting RequestsRetrieves all reporting requests for the account with their current status and download URLs.
List SessionsList Quaderno Checkout sessions with optional filtering and pagination.
List Tax CodesTool to list all supported tax codes.
List WebhooksTool to list all webhooks.
Mark Invoice UncollectibleTool to mark an invoice as uncollectible (bad debt).
Ping API ServiceTool to check if the Quaderno API service is up and verify credentials.
Record Invoice PaymentTool to record a payment on an existing invoice.
Remove Invoice PaymentTool to remove a payment from an invoice.
Retrieve ContactTool to retrieve details of an existing contact by ID.
Retrieve Contact by Processor IDTool to retrieve a contact by external payment processor customer ID and gateway name.
Retrieve CouponRetrieve detailed information about a specific coupon by its ID.
Retrieve Credit NoteTool to retrieve details of an existing credit note by ID.
Retrieve EvidenceRetrieves a specific evidence object by its ID.
Retrieve ExpenseTool to retrieve details of an existing expense 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.
Retrieve ReceiptTool to retrieve details of an existing receipt by ID.
Retrieve RecurringTool to retrieve details of an existing recurring document by ID.
Retrieve Reporting RequestTool to retrieve the status and download URL of a specific report request by ID.
Retrieve Tax CodeTool to retrieve a specific tax code by ID.
Retrieve Tax IDTool to retrieve details of a specific tax ID by its ID.
Update ContactTool to update an existing contact in Quaderno.
Update CouponTool to update an existing coupon.
Update Credit NoteTool to update a credit note.
Update EstimateUpdates an existing estimate in Quaderno by modifying allowed fields.
Update EvidenceTool to update an evidence object.
Update ExpenseUpdates an existing expense in Quaderno by modifying allowed fields.
Update InvoiceUpdates an existing invoice in Quaderno by modifying allowed fields.
Update productTool to update a product; unspecified fields remain unchanged.
Update RecurringTool to update a recurring document in Quaderno.
Update Tax IDTool to update an existing tax ID in Quaderno.
Update WebhookTool to update an existing webhook configuration.
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 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

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Quaderno account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Quaderno

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Quaderno access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called quaderno_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["quaderno"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Quaderno actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Quaderno actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, quaderno)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Quaderno tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Quaderno database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Quaderno

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Quaderno, then start asking questions.

Complete Code

Here's the complete code to get you started with Quaderno and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["quaderno"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Quaderno actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Quaderno actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Quaderno to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Quaderno tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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 LlamaIndex?

Yes, you can. LlamaIndex 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.

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