How to integrate Workday MCP with CrewAI

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Introduction

This guide walks you through connecting Workday to CrewAI using the Composio tool router. By the end, you'll have a working Workday agent that can request vacation days for next week, check my current absence balance, find all open job postings i manage, summarize feedback from recent interviews through natural language commands.

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

The Workday MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Workday account. It provides structured and secure access to your HR, payroll, and recruiting data, so your agent can perform actions like managing time off, retrieving employee details, tracking job postings, and analyzing interview feedback on your behalf.

  • Automated time off management: Easily create new time off requests or check absence balances for yourself or others, making leave management effortless.
  • Employee data and profile retrieval: Have your agent fetch profile details for the current user or any specified worker to simplify onboarding and HR processes.
  • Comprehensive job posting insights: Instantly retrieve information about job postings, including descriptions and screening questionnaires, to aid recruiters and hiring managers.
  • Interview feedback analysis: Let your agent pull and summarize interview feedback entries to streamline debriefs and improve hiring decisions.
  • Access to holiday and leave events: Quickly get holiday schedules and leave status values for better workforce planning and scheduling.

Supported Tools & Triggers

Tools
Create Time Off RequestCreates a time off request for the specified worker id and initiates the business process.
Get Absence BalanceRetrieves the specified balance of all absence plan and leave of absence types.
Get Balance DetailsRetrieves the specified balance of all absence plan and leave of absence types.
Get Current UserRetrieves the current authenticated worker's profile information from workday.
Get Holiday EventsReturns the holiday events for the specified workers and time period.
Get Interview FeedbackRetrieves feedback entries for a specific interview to prepare debrief notes with highlights and lowlights.
Get Job PostingRetrieves detailed information about a specific job posting including job description.
Get Job Posting QuestionnaireRetrieves screening questions and questionnaires associated with a specific job posting.
Get Leave Status ValuesRetrieves instances that can be used as values for other endpoint parameters in this service.
Get My Job PostingsFinds all job postings assigned to a specific recruiter by analyzing interviews and job requisitions.
Get ProspectRetrieves a single prospect instance for talent matching and best-fit analysis.
Get Prospect EducationsRetrieves the education of a prospect for talent matching and best-fit analysis.
Get Prospect ExperiencesRetrieves the work experience of a prospect for talent matching and best-fit analysis.
Get Prospect Resume AttachmentsRetrieves resume attachments for a specific prospect to help prepare for upcoming interviews.
Get Prospect SkillsRetrieves the skills of a prospect for talent matching and best-fit analysis.
Get Time Off Status ValuesRetrieves instances that can be used as values for other endpoint parameters in this service.
Get Worker Eligible Absence TypesRetrieves a collection of eligible absence types for the specified worker.
Get Worker Leaves of AbsenceRetrieves the leaves of absence for the specified worker using the working absencemanagement v1 api.
Get Worker Time Off DetailsRetrieves a collection of time off details for the specified worker.
Get Worker Valid Time Off DatesRetrieves the valid time off dates for the specified worker id for the given dates.
List Absence BalancesRetrieves the balance of all absence plan and leave of absence type for the specified worker id.
List BalancesRetrieves the balance of all absence plan and leave of absence type for the specified worker id.
List InterviewsRetrieves a list of interviews with job requisition and recruiter assignment details.
List Job PostingsRetrieves a list of job postings from workday recruiting system with filtering options.
List WorkersRetrieves a collection of workers and current staffing information.

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 Workday 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[mcp] python-dotenv
What's happening:
  • composio connects your agent to Workday via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] 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
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
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 Workday MCP URL

Create a Composio Tool Router session for Workday

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["workday"])

url = session.mcp.url
What's happening:
  • You create a Workday only session through Composio
  • Composio returns an MCP HTTP URL that exposes Workday tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[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:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

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

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["workday"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Workday through Composio's Tool Router. The agent can perform Workday 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 Workday MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Workday MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Workday MCP with Claude Agent SDK

Google ADK

Google ADK

Use Workday MCP with Google ADK

LangChain

LangChain

Use Workday MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Workday MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Workday MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Workday MCP with LlamaIndex

Claude Code

Claude Code

Use Workday MCP with Claude Code

FAQ

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

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

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

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

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