How to integrate Forcemanager MCP with Pydantic AI

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Introduction

This guide walks you through connecting Forcemanager to Pydantic AI 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 through natural language commands.

This guide will help you understand how to give your Pydantic AI 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.

Also integrate Forcemanager with

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Forcemanager
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Forcemanager workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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  • Activity management and retrieval: Instantly fetch specific sales activities or remove outdated ones, helping you keep your team's daily records up to date.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 ContactPermanently deletes a contact from ForceManager by its unique ID.
Delete Sales OrderDelete a sales order by ID using ForceManager REST API.
Delete Sales Order LineDelete a sales order line by ID.
Delete Master Data ValueDelete a master-data value (Z_ table) by ID using ForceManager REST API.
Delete ViewDelete a saved view (custom filter) by its ID.
Get ActivityRetrieves a single activity by its ID from ForceManager CRM.
Get CompanyRetrieve a single company by its ID from ForceManager.
Get Internal IDTool to retrieve ForceManager internal IDs mapping for a given externalId and entity type.
Get ProductRetrieve a single product by its ID from ForceManager/Sage Sales Management.
Get Sales Order LineRetrieves a single sales order line by ID from ForceManager.
Get UserRetrieves a single ForceManager user by their ID, returning comprehensive user information including name, email, phone, active status, permission level, manager, branches, and more.
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 ProductUpdates an existing 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 Composio SDK?

Composio's Composio SDK 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 Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK 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 with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Forcemanager
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Forcemanager
  • MCPServerStreamableHTTP connects to the Forcemanager MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Forcemanager
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["forcemanager"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Forcemanager tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
forcemanager_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[forcemanager_mcp],
    instructions=(
        "You are a Forcemanager assistant. Use Forcemanager tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Forcemanager endpoint
  • The agent uses GPT-5 to interpret user commands and perform Forcemanager operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Forcemanager.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Forcemanager API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Forcemanager
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["forcemanager"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    forcemanager_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[forcemanager_mcp],
        instructions=(
            "You are a Forcemanager assistant. Use Forcemanager tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Forcemanager.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Forcemanager through Composio's Tool Router. With this setup, your agent can perform real Forcemanager actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Forcemanager for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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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 Pydantic AI?

Yes, you can. Pydantic AI 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.

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