How to integrate Jobnimbus MCP with OpenAI Agents SDK

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 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.

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Api Key

JobNimbus is a CRM and project management platform built for contractors. It streamlines scheduling, estimates, invoicing, and job tracking to simplify your workflow.

21 Tools

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 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.

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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 OpenAI 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.

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

Step by step09 STEPS
1

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
2

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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

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.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
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.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Jobnimbus
const session = await composio.create(userId as string, {
  toolkits: ['jobnimbus'],
});
const mcpUrl = 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.
8

Configure the agent

// Configure agent with MCP tool
const agent = new 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({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: '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 object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Jobnimbus operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
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 run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Jobnimbus and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['jobnimbus'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new 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({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

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.
TOOLS

Supported Tools

Every Jobnimbus action and event your agent gets out of the box.

Create Location

Tool to create a new location in JobNimbus.

Get Account Settings

Tool to retrieve account-wide settings (workflows, types, sources).

Get Activity by ID

Retrieves a specific JobNimbus activity by its unique jnid.

Get Contact by ID

Tool to retrieve a contact by ID.

List Contacts

Tool to list all contacts.

Update Contact

Tool to update an existing contact.

Create File Attachment Type

Creates a new file attachment type in JobNimbus.

Create Material Order

Creates a new material order in JobNimbus.

Create Task

Tool to create a new task.

Create Workflow Status

Tool to create a new status in an existing workflow.

Get File Attachment Content by ID

Retrieves the raw content of a specific file attachment from JobNimbus by its unique ID.

List Activities

Tool to retrieve all activities.

List Invoices

Tool to list all invoices (v2).

List Material Orders

Tool to list all material orders (v2).

List Payments

Tool to retrieve payments list with optional filters.

List Products

Tool to list all products.

List Work Orders

Tool to retrieve all work orders (v2).

Get Product by ID

Retrieves detailed information about a specific JobNimbus product using its jnid.

List Tasks

Tool to list all tasks.

Update Task

Update an existing JobNimbus task by its jnid.

Get Units of Measure

Tool to retrieve list of supported units of measure.

FAQ

Frequently asked questions

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.

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.

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.

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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