How to integrate Jobnimbus MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Jobnimbus to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Jobnimbus agent that can list all open tasks for this week, create a new material order for a contact, fetch details for contact by name, add a custom file attachment type through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Jobnimbus account through Composio's Jobnimbus 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 and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Jobnimbus
  • Configure an AI agent that can use Jobnimbus as a tool
  • Run a live chat session where you can ask the agent to perform Jobnimbus operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Jobnimbus MCP server, and what's possible with it?

The Jobnimbus MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Jobnimbus account. It provides structured and secure access to your CRM and project management data, so your agent can perform actions like managing contacts, scheduling tasks, creating locations, and retrieving account information on your behalf.

  • Contact management and lookup: Instantly create new contacts or fetch full details and lists of existing contacts for streamlined project tracking and reporting.
  • Task scheduling and tracking: Direct your agent to create and assign tasks, helping teams stay organized and on top of project to-dos.
  • Location and job site creation: Quickly add new locations to your Jobnimbus account, ensuring every job and address is properly logged for future reference.
  • Material order and workflow automation: Let your agent place material orders for jobs and update workflow statuses to keep projects moving smoothly from lead to completion.
  • Account and attachment management: Retrieve account settings or pull file attachments by ID, supporting seamless document handling and system configuration.

Supported Tools & Triggers

Tools
Create LocationTool to create a new location in jobnimbus.
Get Activity by IDTool to retrieve a specific activity by its id.
Get Contact by IDTool to retrieve a contact by id.
List ContactsTool to list all contacts.
Create File Attachment TypeTool to create a new file attachment type.
Create Material OrderTool to create a new material order (v2).
Create TaskTool to create a new task.
Create Workflow StatusTool to create a new status in an existing workflow.
Get File Attachment by IDTool to retrieve a specific file attachment's raw content by id.
Get Account SettingsTool to retrieve account-wide settings (workflows, types, sources).
Update ContactTool to update an existing contact.
List TasksTool to list all tasks.
List ActivitiesTool to retrieve all activities.
List InvoicesTool to list all invoices (v2).
List Material OrdersTool to list all material orders (v2).
List PaymentsTool to retrieve payments list with optional filters.
List ProductsTool to list all products.
List Work OrdersTool to retrieve all work orders (v2).
Get Product by IDTool to retrieve a specific product by id (v2).
Update TaskTool to update an existing task.
Get Units of MeasureTool to retrieve list of supported units of measure.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Jobnimbus project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Jobnimbus.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Jobnimbus Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["jobnimbus"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only jobnimbus.
  • The router checks the user's Jobnimbus connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Jobnimbus.
  • This approach keeps things lightweight and lets the agent request Jobnimbus tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Jobnimbus. "
        "Help users perform Jobnimbus operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Jobnimbus and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Jobnimbus operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Jobnimbus.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Jobnimbus and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["jobnimbus"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Jobnimbus. "
        "Help users perform Jobnimbus operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Jobnimbus MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Jobnimbus.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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FAQ

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

With a standalone Jobnimbus MCP server, the agents and LLMs can only access a fixed set of Jobnimbus tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Jobnimbus and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Jobnimbus tools.

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

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

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