How to integrate Mx technologies MCP with CrewAI

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Introduction

This guide walks you through connecting Mx technologies to CrewAI using the Composio tool router. By the end, you'll have a working Mx technologies agent that can create a manual account for a user, list account numbers for a specific member, fetch rewards for a connected member, get a configurable widget url for a user through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Mx technologies account through Composio's Mx technologies 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 Mx technologies connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Mx technologies
  • Build a conversational loop where your agent can execute Mx technologies 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 Mx technologies MCP server, and what's possible with it?

The Mx technologies MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mx technologies account. It provides structured and secure access to financial data aggregation and account management features, so your agent can perform actions like creating accounts, managing members, fetching financial rewards, and handling account ownership on your behalf.

  • Automated account creation and management: Let your agent create new manual accounts, partner accounts, and user SSO accounts for seamless onboarding and testing.
  • Member aggregation and connection: Instruct your agent to create members and initiate aggregation of financial products across institutions, streamlining financial data collection.
  • Rewards and incentives tracking: Have your agent fetch and aggregate member rewards data after account connections, so you never miss out on incentives.
  • Secure access to account details: Direct your agent to list account owners, retrieve account numbers by member, and access configurable widget URLs for enhanced user interactions.
  • Credential and API management: Use your agent to retrieve API credentials for audience services, streamlining authentication flows and integrations.

Supported Tools & Triggers

Tools
Cancel Partner AccountTool to cancel (disable) a client account under a partner account.
Create accountTool to create a manual account for a given user.
Retrieve Audience API CredentialsTool to retrieve audience api credentials.
Create memberTool to create a member and start aggregating specified financial products.
Create Partner AccountTool to create a new client account under a partner account.
Create Partner Account User SSOTool to create a new partner account user with single sign-on enabled.
Fetch rewardsTool to initiate rewards aggregation for a specific member.
Get configurable widget URLTool to retrieve a configurable widget url for a user.
List Account Numbers by MemberTool to list account numbers for a specific member.
List account ownersTool to list account owners associated with a member's account.
List account owners by memberTool to list account owners for a specific member.
List accountsTool to list all accounts for a user.
List budgetsTool to list budgets for a specific user.
List categoriesTool to list all categories for a user.
List challengesTool to list mfa challenges for a member.
List Connect Widget URLsTool to list connect widget urls for a user.
List favorite institutionsTool to list partner favorite institutions, sorted by popularity.
List goalsTool to list goals for a specific user.
List institution credentialsTool to list credential fields required by a given institution.
List institutionsTool to list financial institutions supported by mx.
List member accountsTool to list accounts for a specific member.
List membersTool to list members associated with a specific user.
List rewardsTool to list rewards associated with a specific user and member.
List statements by memberTool to list statements for a member.
List taggingsTool to list all taggings for a specific user.
List tagsTool to list all tags for a user.
List transactionsTool to list transactions for a user.
List transactions by memberTool to list transactions for a member.
List usersTool to list users.
Read accountTool to retrieve details for a specific account.
Read account balanceTool to retrieve the available balance for a specific account.
Read categoryTool to retrieve a default category by guid.
Read FDX accountTool to return details for the specified fdx account.

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 Mx technologies 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 Mx technologies 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 Mx technologies MCP URL

Create a Composio Tool Router session for Mx technologies

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["mx_technologies"],
)
url = session.mcp.url
What's happening:
  • You create a Mx technologies only session through Composio
  • Composio returns an MCP HTTP URL that exposes Mx technologies 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="Mx technologies Assistant",
    goal="Help users interact with Mx technologies through natural language commands",
    backstory=(
        "You are an expert assistant with access to Mx technologies tools. "
        "You can perform various Mx technologies 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 Mx technologies 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 Mx technologies 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 Mx technologies 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_mx_technologies_agent.py

Complete Code

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

python
# file: crewai_mx_technologies_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 Mx technologies session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["mx_technologies"],
    )
    url = session.mcp.url

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

    # Create Mx technologies assistant agent
    toolkit_agent = Agent(
        role="Mx technologies Assistant",
        goal="Help users interact with Mx technologies through natural language commands",
        backstory=(
            "You are an expert assistant with access to Mx technologies tools. "
            "You can perform various Mx technologies 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 Mx technologies 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 Mx technologies 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 Mx technologies through Composio's Tool Router. The agent can perform Mx technologies 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 Mx technologies MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Mx technologies MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Mx technologies MCP with Claude Agent SDK

Google ADK

Google ADK

Use Mx technologies MCP with Google ADK

LangChain

LangChain

Use Mx technologies MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Mx technologies MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Mx technologies MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Mx technologies MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Mx technologies MCP?

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

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

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

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