How to integrate Forcemanager MCP with CrewAI

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Introduction

This guide walks you through connecting Forcemanager to CrewAI using the Composio tool router. By the end, you'll have a working Forcemanager agent that can delete a contact by their id, get details for a specific sales order, retrieve company info using company id, delete a saved view for my team through natural language commands.

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

The Forcemanager MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Forcemanager account. It provides structured and secure access to your CRM data, so your agent can perform actions like retrieving activity details, managing companies and contacts, and organizing sales orders on your behalf.

  • Activity management and retrieval: Instantly fetch specific sales activities or remove outdated ones, helping you keep your team's daily records up to date.
  • Company and contact administration: Easily get detailed company or contact information, or delete records when they're no longer needed—all with your agent's help.
  • Sales order and line control: Let your agent delete sales orders or individual order lines, streamlining your sales workflow and keeping data clean.
  • Master data maintenance: Empower your agent to manage master-data values, ensuring your CRM stays accurate and relevant as your business evolves.
  • Saved view organization: Ask your agent to delete saved views you no longer use, keeping your workspace focused and clutter-free.

Supported Tools & Triggers

Tools
Delete ActivityDelete an existing activity by ID.
Delete CompanyTool to delete a company by its ForceManager ID.
Delete ContactDelete an existing contact by ID.
Delete Sales OrderDelete a sales order by ID using ForceManager REST API.
Delete Sales Order LineDelete a sales order line by ID using ForceManager REST API.
Delete Master Data ValueDelete a master-data value (Z_ table) by ID using ForceManager REST API.
Delete ViewDelete a saved view by ID.
Get ActivityTool to get a single activity by ID.
Get CompanyTool to get a single company by ID.
Get Internal IDTool to retrieve ForceManager internal IDs mapping for a given externalId and entity type.
Get ProductTool to get a single product by ID.
Get Sales Order LineTool to get a single sales order line by ID.
Get UserTool to get a single user by ID.
Get ViewTool to get a single view by ID.
List ViewsTool to list saved view filters.
Update ActivityTool to update an existing activity by ID.
Update CompanyUpdate Company
Update ProductTool to update a product by ID in ForceManager.
Update Sales OrderUpdate Sales Order
Update Sales Order LineTool to update sales order line 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 Forcemanager 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 Forcemanager 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 Forcemanager MCP URL

Create a Composio Tool Router session for Forcemanager

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

Complete Code

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

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

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

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

OpenAI Agents SDK

OpenAI Agents SDK

Use Forcemanager MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Forcemanager MCP with Claude Agent SDK

Google ADK

Google ADK

Use Forcemanager MCP with Google ADK

LangChain

LangChain

Use Forcemanager MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Forcemanager MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Forcemanager MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Forcemanager MCP with LlamaIndex

FAQ

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

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

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

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

Used by agents from

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