How to integrate Recruitee MCP with Pydantic AI

This guide walks you through connecting Recruitee to Pydantic AI using the Composio tool router. By the end, you'll have a working Recruitee agent that can add a new candidate named alex lee, list all currently published job offers, get detailed profile for candidate emily chen through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Recruitee account through Composio's Recruitee MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Recruitee is collaborative hiring software that centralizes recruitment tasks for teams. It streamlines sourcing, interviewing, and hiring so you can fill roles faster.

23 Tools

Introduction

This guide walks you through connecting Recruitee to Pydantic AI using the Composio tool router. By the end, you'll have a working Recruitee agent that can add a new candidate named alex lee, list all currently published job offers, get detailed profile for candidate emily chen through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Recruitee account through Composio's Recruitee MCP server.

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

Also integrate Recruitee with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 Recruitee
  • 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 Recruitee 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 Recruitee MCP server, and what's possible with it?

The Recruitee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Recruitee account. It provides structured and secure access to your recruitment workflow, so your agent can perform actions like managing candidates, creating notes, publishing job offers, retrieving company info, and handling tags on your behalf.

  • Automated candidate management: Quickly create new candidate profiles, retrieve detailed information, or delete candidates as your hiring process evolves.
  • Collaborative note-taking: Let your agent add notes to candidate profiles, ensuring every piece of feedback or interview insight is captured and accessible.
  • Job offer publishing and retrieval: Effortlessly generate new job offers or fetch details on published positions from your public careers site.
  • Company and job listing access: Instantly get your company ID, list all candidates, or pull a list of current published job offers for reporting and coordination.
  • Tag and label management: Enable your agent to delete outdated tags, keeping your recruitment database organized and relevant.

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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
  • 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.
3

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 Recruitee
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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
5

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 Recruitee
  • MCPServerStreamableHTTP connects to the Recruitee MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Recruitee
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["recruitee"],
    )
    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 Recruitee 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
recruitee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[recruitee_mcp],
    instructions=(
        "You are a Recruitee assistant. Use Recruitee tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Recruitee endpoint
  • The agent uses GPT-5 to interpret user commands and perform Recruitee operations
  • The instructions field defines the agent's role and behavior
8

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 Recruitee.\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
  • Recruitee API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Recruitee 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 Recruitee
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["recruitee"],
    )
    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
    recruitee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[recruitee_mcp],
        instructions=(
            "You are a Recruitee assistant. Use Recruitee 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 Recruitee.\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 Recruitee through Composio's Tool Router. With this setup, your agent can perform real Recruitee 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 + Recruitee for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Create Candidate

Tool to create a new candidate profile.

Create Note

Creates a new note for a candidate in Recruitee.

Create Offer

Creates a new job offer or talent pool in Recruitee.

Delete Candidate

Tool to delete a candidate profile.

Delete Tag

Permanently deletes a tag from Recruitee by its ID.

Get Candidate

Tool to retrieve detailed information about a specific candidate.

Get Candidates

Tool to retrieve a list of all candidates in the company.

Get Company ID

Tool to retrieve the company ID of the authenticated account.

Get Company Offer Public

Tool to retrieve a specific published job offer by ID or slug from the public Careers Site API.

Get Departments

Tool to retrieve a list of company departments.

Get Locations

Tool to retrieve a list of company locations.

Get Notes

Tool to retrieve a list of notes for a specific candidate.

Get Offers

Tool to retrieve a list of all job offers.

Get Pipeline Stages

Tool to retrieve pipeline stages of a job offer.

Get Tags

Retrieve all tags with optional filtering and pagination.

List EEO Job Categories

Tool to retrieve available EEO (Equal Employment Opportunity) job categories.

List Invoices

Tool to list invoices for a company.

List Localization Settings

Tool to retrieve localization settings including proposed time format and start day of the week.

List Share Countries

Tool to retrieve all countries with region codes and phone codes per locale.

List Share EEO Answers

Tool to retrieve available EEO (Equal Employment Opportunity) answers.

Update Candidate

Updates an existing candidate's information in Recruitee.

Update Note

Tool to update an existing note for a candidate.

Update Offer

Updates an existing job offer or talent pool in Recruitee.

FRAMEWORKS

How to build Recruitee MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Recruitee MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Recruitee MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Recruitee MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Recruitee MCP with Claude Cowork

Codex logo

Codex

Use Recruitee MCP with Codex

OpenClaw logo

OpenClaw

Use Recruitee MCP with OpenClaw

Hermes logo

Hermes

Use Recruitee MCP with Hermes

CLI logo

CLI

Use Recruitee MCP with CLI

Google ADK logo

Google ADK

Use Recruitee MCP with Google ADK

LangChain logo

LangChain

Use Recruitee MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Recruitee MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Recruitee MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Recruitee MCP with LlamaIndex

CrewAI logo

CrewAI

Use Recruitee MCP with CrewAI

FAQ

Frequently asked questions

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

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 Recruitee tools.

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

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