How to integrate Moneybird MCP with CrewAI

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Introduction

This guide walks you through connecting Moneybird to CrewAI using the Composio tool router. By the end, you'll have a working Moneybird agent that can create a sales invoice for a new client, filter contacts added this month, add a note to a specific contact, archive a contact no longer in use through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Moneybird account through Composio's Moneybird 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 a Composio API key and configure your Moneybird connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Moneybird
  • Build a conversational loop where your agent can execute Moneybird operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Moneybird MCP server, and what's possible with it?

The Moneybird MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Moneybird account. It provides structured and secure access to your invoicing and accounting data, so your agent can perform actions like creating contacts, sending invoices, managing notes, and keeping your financial records up to date on your behalf.

  • Automated contact creation and management: Instantly add new clients or companies, update existing records, archive unused contacts, or remove outdated information—without manual entry.
  • Easy invoice generation: Direct your agent to create detailed sales invoices for any contact, including custom line items, for fast and accurate billing.
  • Contact note and to-do tracking: Record comments, assign to-dos, and manage notes on contacts, ensuring follow-ups and client history are always at your fingertips.
  • Contact filtering and segmentation: Effortlessly filter and retrieve contacts based on criteria like creation date or name, making it easy to target communications or review segments of your client base.
  • Comprehensive contact person management: Add or remove individual contact persons linked to organizations, keeping your records detailed and up to date for every client relationship.

Supported Tools & Triggers

Tools
Add Note to ContactTool to add a note or to-do to a contact.
Archive ContactTool to archive a contact.
Create Moneybird ContactTool to create a new contact in moneybird.
Create Contact PersonTool to create a new contact person.
Create Sales InvoiceTool to create a new sales invoice.
Delete ContactTool to delete a contact.
Delete Contact NoteTool to delete a note from a contact.
Delete Contact PersonTool to delete a contact person from a contact.
Filter ContactsTool to filter contacts.
Get Additional ChargesTool to get additional charges for a contact.
Get ContactTool to retrieve all information about a specific contact by id.
Get Contact by Customer IDTool to retrieve full contact details by customer id.
Get Contact PersonTool to get all information about a contact person.
Get Sales InvoiceTool to get a single sales invoice by id.
List AdministrationsTool to list all administrations accessible by the authenticated user.
List Contacts SynchronizationTool to list all contact ids and versions for synchronization.
List Sales InvoicesTool to list all sales invoices in an administration.
Request Payments Mandate URLTool to request a url for setting up a payments mandate.
Update ContactTool to update a contact.
Update Contact PersonTool to update a contact person.
Update Sales InvoiceTool to update an existing sales invoice by id.

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 and API key
  • A Moneybird connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Moneybird via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Moneybird MCP URL

Create a Composio Tool Router session for Moneybird

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["moneybird"],
)
url = session.mcp.url
What's happening:
  • You create a Moneybird only session through Composio
  • Composio returns an MCP HTTP URL that exposes Moneybird tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Moneybird Assistant",
    goal="Help users interact with Moneybird through natural language commands",
    backstory=(
        "You are an expert assistant with access to Moneybird tools. "
        "You can perform various Moneybird operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Moneybird MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Moneybird operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Moneybird related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_moneybird_agent.py

Complete Code

Here's the complete code to get you started with Moneybird and CrewAI:

python
# file: crewai_moneybird_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Moneybird session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["moneybird"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Moneybird assistant agent
    toolkit_agent = Agent(
        role="Moneybird Assistant",
        goal="Help users interact with Moneybird through natural language commands",
        backstory=(
            "You are an expert assistant with access to Moneybird tools. "
            "You can perform various Moneybird operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Moneybird operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Moneybird related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Moneybird through Composio's Tool Router. The agent can perform Moneybird operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Moneybird MCP Agent with another framework

FAQ

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

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Moneybird tools.

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

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

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

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