How to integrate Dynamics365 MCP with CrewAI

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Introduction

This guide walks you through connecting Dynamics365 to CrewAI using the Composio tool router. By the end, you'll have a working Dynamics365 agent that can create a new sales lead for acme corp, list all open invoices for this quarter, add a support case for a specific customer, generate a new sales order for an existing account through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Dynamics365 account through Composio's Dynamics365 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 Dynamics365 connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Dynamics365
  • Build a conversational loop where your agent can execute Dynamics365 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 Dynamics365 MCP server, and what's possible with it?

The Dynamics365 MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dynamics365 account. It provides structured and secure access to your CRM data, so your agent can perform actions like managing contacts, creating leads, tracking invoices, and automating sales workflows on your behalf.

  • Automated contact, account, and lead creation: Instantly add new contacts, accounts, or leads to your CRM, ensuring your pipeline stays up to date with zero manual data entry.
  • Sales opportunity and order management: Let your agent create and update opportunities or sales orders, helping your team stay organized and focused on closing deals.
  • Invoice and case tracking: Retrieve, create, or manage invoices and cases directly from Dynamics365, streamlining customer service and billing operations.
  • Real-time CRM record retrieval: Ask your agent to fetch specific leads, invoices, or cases by criteria, so you always have the most relevant customer data at your fingertips.
  • Seamless workflow automation: Combine multiple actions—like creating a lead, generating an invoice, and opening a case—into a single smooth workflow, all triggered by your agent.

Supported Tools & Triggers

Tools
Get all invoices actionGet all invoices action
Create AccountCreates a new account entity record in dynamics crm using the web api.
Create CaseCreates a new case (incident) entity record in dynamics crm using the web api.
Create ContactCreates a new contact entity record in dynamics crm using the web api.
Create InvoiceCreates a new invoice entity record in dynamics crm using the web api.
Create LeadCreates a new lead entity record in dynamics crm using the web api.
Create OpportunityCreates a new opportunity entity record in dynamics crm using the web api.
Create Sales OrderCreates a new sales order entity record in dynamics crm using the web api.
Dynamicscrm get a invoiceDynamicscrm get a invoice
Dynamicscrm get a leadDynamicscrm get a lead
Dynamicscrm get all leadsDynamicscrm get all leads
Update CaseUpdates an existing case (incident) entity record in dynamics crm using the web api.
Update InvoiceUpdates an existing invoice entity record in dynamics crm using the web api.
Update LeadUpdates an existing lead entity record in dynamics crm using the web api.
Update OpportunityUpdates an existing opportunity entity record in dynamics crm using the web api.
Update Sales OrderUpdates an existing sales order entity record in dynamics crm using the web api.

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 Dynamics365 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 Dynamics365 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 Dynamics365 MCP URL

Create a Composio Tool Router session for Dynamics365

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["dynamics365"],
)
url = session.mcp.url
What's happening:
  • You create a Dynamics365 only session through Composio
  • Composio returns an MCP HTTP URL that exposes Dynamics365 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="Dynamics365 Assistant",
    goal="Help users interact with Dynamics365 through natural language commands",
    backstory=(
        "You are an expert assistant with access to Dynamics365 tools. "
        "You can perform various Dynamics365 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 Dynamics365 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 Dynamics365 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 Dynamics365 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_dynamics365_agent.py

Complete Code

Here's the complete code to get you started with Dynamics365 and CrewAI:

python
# file: crewai_dynamics365_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 Dynamics365 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["dynamics365"],
    )
    url = session.mcp.url

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

    # Create Dynamics365 assistant agent
    toolkit_agent = Agent(
        role="Dynamics365 Assistant",
        goal="Help users interact with Dynamics365 through natural language commands",
        backstory=(
            "You are an expert assistant with access to Dynamics365 tools. "
            "You can perform various Dynamics365 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 Dynamics365 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 Dynamics365 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 Dynamics365 through Composio's Tool Router. The agent can perform Dynamics365 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 Dynamics365 MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Dynamics365 MCP?

With a standalone Dynamics365 MCP server, the agents and LLMs can only access a fixed set of Dynamics365 tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dynamics365 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 Dynamics365 tools.

Can I manage the permissions and scopes for Dynamics365 while using Tool Router?

Yes, absolutely. You can configure which Dynamics365 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 Dynamics365 data and credentials are handled as safely as possible.

Used by agents from

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ASU
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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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