How to integrate Servicem8 MCP with CrewAI

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Introduction

This guide walks you through connecting Servicem8 to CrewAI using the Composio tool router. By the end, you'll have a working Servicem8 agent that can create a new job for a plumbing callout, list all clients with overdue invoices, add a payment note to job 12345, show all available job document templates through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Servicem8 account through Composio's Servicem8 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 Servicem8 connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Servicem8
  • Build a conversational loop where your agent can execute Servicem8 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 Servicem8 MCP server, and what's possible with it?

The Servicem8 MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Servicem8 account. It provides structured and secure access to your job management system, so your agent can perform actions like creating jobs, managing notes and payments, listing clients, and retrieving templates on your behalf.

  • Job creation and management: Instruct your agent to create new jobs, add detailed job information, or update records, streamlining field service operations.
  • Automated note handling: Have your agent attach important notes to jobs or remove outdated notes to keep job records clean and up-to-date.
  • Payment processing and tracking: Let your agent record new job payments or archive payment records, ensuring accurate and timely invoicing.
  • Comprehensive client and asset retrieval: Ask your agent to pull complete lists of clients and assets for reporting, integrations, or inventory management.
  • Template and form discovery: Fetch available document templates and forms so your agent can prepare job paperwork or gather required information efficiently.

Supported Tools & Triggers

Tools
ServiceM8 Create Job NoteTool to create a new job note in servicem8.
ServiceM8 Create Job PaymentTool to create a new job payment in servicem8.
Create a new JobTool to create a new job in servicem8.
Delete Job NoteTool to delete a specific job note.
ServiceM8 Delete Job PaymentTool to delete (archive) a specific job payment by its uuid.
List All AssetsTool to list all servicem8 assets.
List All ClientsTool to list all servicem8 clients.
List All Document TemplatesTool to list document templates.
List All FormsTool to list all servicem8 forms.
List All Job NotesTool to list all job notes in servicem8.
List All Job QueuesTool to list all job queues in servicem8.
List All JobsTool to list all jobs.
List All LocationsTool to list all servicem8 locations.
List All MaterialsTool to list all materials.
List All TasksTool to list all tasks in a servicem8 account.
Retrieve ServiceM8 ClientTool to retrieve details of a specific client by its uuid.
Retrieve FormTool to retrieve details of a specific form by its uuid.
Retrieve JobTool to retrieve details of a specific job by its uuid.
Retrieve Job ActivityTool to retrieve details of a specific job activity by its uuid.
Retrieve Job NoteTool to retrieve details of a specific job note by its uuid.
Retrieve Job PaymentTool to retrieve details of a specific job payment by its uuid.
Retrieve Job QueueTool to retrieve details of a specific job queue by its uuid.
Retrieve LocationTool to retrieve details of a specific location by its uuid.
Retrieve ServiceM8 MaterialTool to retrieve details of a specific material by its uuid.
Retrieve Staff MemberTool to retrieve details of a specific staff member by their uuid.
ServiceM8 Create JobTool to create a new job in servicem8.
Update a ServiceM8 Job NoteTool to update details of an existing job note.
ServiceM8 Update Job PaymentTool to update details of an existing job payment.

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 Servicem8 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 Servicem8 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 Servicem8 MCP URL

Create a Composio Tool Router session for Servicem8

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["servicem8"],
)
url = session.mcp.url
What's happening:
  • You create a Servicem8 only session through Composio
  • Composio returns an MCP HTTP URL that exposes Servicem8 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="Servicem8 Assistant",
    goal="Help users interact with Servicem8 through natural language commands",
    backstory=(
        "You are an expert assistant with access to Servicem8 tools. "
        "You can perform various Servicem8 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 Servicem8 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 Servicem8 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 Servicem8 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_servicem8_agent.py

Complete Code

Here's the complete code to get you started with Servicem8 and CrewAI:

python
# file: crewai_servicem8_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 Servicem8 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["servicem8"],
    )
    url = session.mcp.url

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

    # Create Servicem8 assistant agent
    toolkit_agent = Agent(
        role="Servicem8 Assistant",
        goal="Help users interact with Servicem8 through natural language commands",
        backstory=(
            "You are an expert assistant with access to Servicem8 tools. "
            "You can perform various Servicem8 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 Servicem8 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 Servicem8 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 Servicem8 through Composio's Tool Router. The agent can perform Servicem8 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 Servicem8 MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Servicem8 MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Servicem8 MCP with Claude Agent SDK

Google ADK

Google ADK

Use Servicem8 MCP with Google ADK

LangChain

LangChain

Use Servicem8 MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Servicem8 MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Servicem8 MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Servicem8 MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Servicem8 MCP?

With a standalone Servicem8 MCP server, the agents and LLMs can only access a fixed set of Servicem8 tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Servicem8 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 Servicem8 tools.

Can I manage the permissions and scopes for Servicem8 while using Tool Router?

Yes, absolutely. You can configure which Servicem8 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 Servicem8 data and credentials are handled as safely as possible.

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