How to integrate Workday MCP with Pydantic AI

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Introduction

This guide walks you through connecting Workday to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Workday
  • 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 Workday 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 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 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 Workday
  • 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 Workday
  • MCPServerStreamableHTTP connects to the Workday 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 Workday
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["workday"],
    )
    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 Workday 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
workday_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[workday_mcp],
    instructions=(
        "You are a Workday assistant. Use Workday tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Workday endpoint
  • The agent uses GPT-5 to interpret user commands and perform Workday 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 Workday.\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
  • Workday 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 Workday 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 Workday
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["workday"],
    )
    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
    workday_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[workday_mcp],
        instructions=(
            "You are a Workday assistant. Use Workday 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 Workday.\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 Workday through Composio's Tool Router. With this setup, your agent can perform real Workday 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 + Workday for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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

CrewAI

CrewAI

Use Workday MCP with CrewAI

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 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 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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