How to integrate Bamboohr MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Bamboohr to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bamboohr agent that can add new dependent for employee john doe, update direct deposit details for sarah smith, log overtime hours for marketing team members through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bamboohr account through Composio's Bamboohr MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Bamboohr with

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 Bamboohr
  • Configure an AI agent that can use Bamboohr as a tool
  • Run a live chat session where you can ask the agent to perform Bamboohr 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 Bamboohr MCP server, and what's possible with it?

The BambooHR MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your BambooHR account. It provides structured and secure access to your HR data, so your agent can perform actions like managing employee benefits, updating payroll records, tracking time, and assisting with applicant management on your behalf.

  • Employee benefits administration: Automatically enroll employees in benefit groups, create or update benefit records, and manage company-wide benefit offerings with ease.
  • Payroll and direct deposit management: Enable your agent to create paystubs, add unpaid pay periods, and update employee direct deposit information for seamless payroll processing.
  • Dependent and tax record updates: Empower your agent to add employee dependents and modify withholding details, keeping employee records accurate and compliant.
  • Time tracking automation: Let your agent log new time tracking records for employees, ensuring precise attendance and overtime data for reporting and payroll.
  • Applicant and recruitment collaboration: Allow your agent to post comments on applicant records, streamlining feedback and communication during the hiring process.

Supported Tools & Triggers

Tools
Create Candidate ApplicationTool to create a candidate application.
Create Job OpeningTool to create a new job opening in BambooHR ATS.
List Job ApplicationsTool to list job applications with optional filters.
Get Benefit CoveragesTool to retrieve standard benefit coverage options.
Get Member Benefit EventsTool to list member benefit events.
Get Company EINsTool to retrieve company Employer Identification Numbers (EINs).
Get Company InformationTool to retrieve company information.
Create File CategoryTool to create new company file categories.
Create Time Off RequestTool to submit a new time off request.
List DatasetsTool to list available datasets via the Datasets API.
Create Employee DependentTool to add a dependent to an employee.
Get All Employee DependentsTool to retrieve all employee dependents.
Create EmployeeTool to create a new employee record.
Create Employee File CategoryTool to create new employee file categories.
Get Changed EmployeesTool to get employees inserted, updated, or deleted since a given timestamp.
List Company FilesTool to list company file categories and their files.
Upload Company FileTool to upload a new company file.
Get All EmployeesRetrieves all employees from the BambooHR employee directory including their basic information and status.
Get Applicant StatusesTool to retrieve applicant statuses.
Get Custom Employee FieldsTool to fetch custom employee field values.
Run Custom ReportTool to run a custom report by ID or ad-hoc fields.
Get EmployeeTool to retrieve detailed information for a specific employee.
Get Employee PhotoTool to retrieve an employee's profile photo by size.
Get Hiring LeadsTool to retrieve potential hiring leads (employees who can manage job openings) for use in creating a new job opening.
Get Job SummariesTool to retrieve a list of ATS job summaries.
Get Departments MetadataTool to list department metadata.
Get Meta DivisionsTool to list all division metadata.
List Employment Status MetadataTool to list all employment status metadata.
Get Meta Job TitlesTool to retrieve job title metadata.
Get Meta LocationsTool to list location metadata.
Get Time-Off Types MetadataTool to list time-off type metadata.
Get ReportTool to fetch a built-in or published report in JSON or other formats.
Get Time-Off BalancesTool to retrieve time-off balances for employees.
Get Time-Off RequestsTool to list time-off requests within a date range.
List Company ReportsTool to list all available company and custom reports.
Get Country OptionsTool to retrieve all available country options.
Get List Field DetailsTool to get details for all list fields.
Get Tabular Fields MetadataTool to list tabular table fields metadata.
Get UsersTool to list active users with basic info.
Update EmployeeTool to update fields on a specified employee record.
Update Time Off RequestTool to update the status of an existing time-off request.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Bamboohr 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 Bamboohr.

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 Bamboohr Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bamboohr"]
)

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 bamboohr.
  • The router checks the user's Bamboohr connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Bamboohr.
  • This approach keeps things lightweight and lets the agent request Bamboohr 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 Bamboohr. "
        "Help users perform Bamboohr 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 Bamboohr 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 Bamboohr 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 Bamboohr.
  • 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 Bamboohr and OpenAI 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=["bamboohr"]
)
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 Bamboohr. "
        "Help users perform Bamboohr 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 Bamboohr MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Bamboohr.

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 Bamboohr MCP?

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

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

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

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