How to integrate Lever MCP with Pydantic AI

This guide walks you through connecting Lever to Pydantic AI using the Composio tool router. By the end, you'll have a working Lever agent that can list all open job postings, get candidate details by email, schedule interview for specific candidate through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Lever account through Composio's Lever MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Get started for free Get a demo

Lever

Api KeyOauth2

Lever is an applicant tracking system that blends sourcing, CRM, and analytics for recruiting. It helps companies scale hiring with collaborative workflows and actionable insights.

64 Tools

Managed auth

Connect Lever without auth hassles

We manage OAuth, API keys, token refresh, and scopes — you just build.

Try for free

Introduction

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

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

Also integrate Lever with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

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 Lever
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 Lever 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 Lever MCP server, and what's possible with it?

The Lever MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Lever account. It provides structured and secure access to your recruiting pipeline, so your agent can perform actions like managing candidates, scheduling interviews, updating job postings, tracking offers, and analyzing hiring metrics on your behalf.

End-to-end candidate management: Let your agent add, update, or move candidates through different stages of your hiring process seamlessly.
Automated interview scheduling: Have the agent create, modify, or cancel interviews and coordinate with both candidates and interviewers to streamline the process.
Job posting and requisition updates: Direct your agent to create new job postings, update existing requisitions, or close filled roles instantly.
Offer and feedback tracking: Enable your agent to manage offer letters, track acceptance rates, and collect structured feedback from interviewers.
Recruiting analytics and reporting: Ask the agent to generate reports on pipeline activity, source effectiveness, and diversity metrics—helping you make data-driven hiring decisions.

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS

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 Lever
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 Lever
MCPServerStreamableHTTP connects to the Lever 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 Lever
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["lever"],
    )
    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 Lever 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
lever_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[lever_mcp],
    instructions=(
        "You are a Lever assistant. Use Lever tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)

What's happening:

The MCP client connects to the Lever endpoint
The agent uses GPT-5 to interpret user commands and perform Lever 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 Lever.\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
Lever 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 Lever 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 Lever
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["lever"],
    )
    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
    lever_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[lever_mcp],
        instructions=(
            "You are a Lever assistant. Use Lever 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 Lever.\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 Lever through Composio's Tool Router. With this setup, your agent can perform real Lever 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 + Lever 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 Lever action and event your agent gets out of the box.

Add Opportunity Links

Tool to add links to a contact associated with an opportunity.

Add Opportunity Sources

Tool to add sources to an opportunity.

Add Opportunity Tags

Tool to add tags to an opportunity.

Create Form Submission

Tool to create a completed profile form submission for a candidate's opportunity profile.

Create Form Template

Tool to create a profile form template for an account.

Create Interview

Tool to create an interview on an externally-managed panel in Lever.

Create Note

Tool to create a note on an opportunity profile or add a threaded comment to an existing note.

Create Opportunity

Tool to create a new candidate opportunity in Lever.

Create Panel

Tool to create a new interview panel for an opportunity.

Create Requisition

Tool to create a new requisition in Lever for tracking hiring needs.

Create Requisition Field

Tool to create a custom requisition field schema for use across requisitions.

Create Requisition Field Option

Tool to add new options to a dropdown requisition field without replacing existing options.

Upload File

Tool to upload a file temporarily to Lever for use with posting applications.

Create User

Tool to create a new user in the Lever system.

Deactivate User

Tool to deactivate a user in the Lever system.

Delete Form Template

Tool to delete a profile form template from account.

Delete Interview

Tool to delete an interview from an opportunity panel.

Delete Note

Tool to delete a note on an opportunity.

Delete Panel

Tool to delete a panel from an opportunity.

Delete Requisition

Tool to delete or archive a requisition from Lever account.

Delete Requisition Field

Tool to delete a requisition field from the account.

Delete Requisition Field Option

Tool to remove specific options from a dropdown requisition field.

Download File

Tool to download a file associated with an opportunity.

Get File Metadata

Tool to retrieve metadata for a single file on an opportunity.

Get Form

Tool to retrieve a specific profile form for an opportunity.

Get Form Template

Tool to retrieve a single form template by unique identifier.

Get Interview

Tool to retrieve a single interview for an opportunity.

Get Note

Tool to retrieve a single note for an opportunity.

Get Opportunity

Tool to retrieve detailed information about a single opportunity.

Get Panel

Tool to retrieve a single interview panel for an opportunity.

Get Requisition

Tool to retrieve detailed information about a single requisition by ID.

Get Requisition Field

Tool to retrieve detailed information about a single custom requisition field by ID.

Get Stage

Tool to retrieve detailed information about a single stage by its UUID.

Get User

Tool to retrieve detailed information about a single user by their UUID.

List Opportunity Files

Tool to list all files on an opportunity.

List Forms

Tool to list all profile forms for an opportunity.

List Form Templates

Tool to list all active form templates.

List Interviews

Tool to list all interviews for an opportunity.

List Notes

Tool to list notes on an opportunity profile.

List Offers

Tool to list offers for an opportunity.

List Opportunities

Tool to list all opportunities in the hiring pipeline.

List Panels

Tool to list all interview panels for an opportunity.

List Postings

Tool to list all job postings including published, internal, closed, draft, pending, and rejected postings.

List Referrals

Tool to list all referrals for an opportunity.

List Requisition Fields

Tool to list all requisition field schemas in your Lever account with optional filtering.

List Requisitions

Tool to list all requisitions with filtering and pagination.

List Opportunity Resumes

Tool to list all resumes for an opportunity.

List Sources

Tool to list all recruitment sources in your Lever account.

List Stages

Tool to retrieve all pipeline stages in your Lever account.

List Tags

Tool to list all tags in your Lever account.

List Users

Tool to retrieve all active users in your Lever account with optional filters.

Reactivate User

Tool to reactivate a previously deactivated user in the Lever system.

Remove Contact Links by Opportunity

Tool to remove links from a contact associated with an opportunity.

Remove Opportunity Sources

Tool to remove sources from an opportunity.

Remove Opportunity Tags

Tool to remove tags from an opportunity.

Update Form Template

Tool to update an existing profile form template.

Update Interview

Tool to update an interview on an externally-managed panel.

Update Note

Tool to update a note on an opportunity profile.

Update Panel

Tool to update an externally-managed panel for an opportunity.

Update Requisition

Tool to update an existing requisition in Lever.

Update Requisition Field

Tool to update an existing requisition field in Lever.

Update Requisition Field Option

Tool to update existing options in a dropdown requisition field without replacing the entire field object.

Update User

Tool to update an existing user in the Lever system.

Upload File to Opportunity

Tool to upload a file permanently to an opportunity.

FRAMEWORKS

How to build Lever MCP Agent with another framework

OpenAI Agents SDK

Use Lever MCP with OpenAI Agents SDK

Claude Agent SDK

Use Lever MCP with Claude Agent SDK

Claude Code

Use Lever MCP with Claude Code

Claude Cowork

Use Lever MCP with Claude Cowork

Codex

Use Lever MCP with Codex

OpenClaw

Use Lever MCP with OpenClaw

Hermes

Use Lever MCP with Hermes

CLI

Use Lever MCP with CLI

Google ADK

Use Lever MCP with Google ADK

LangChain

Use Lever MCP with LangChain

Vercel AI SDK

Use Lever MCP with Vercel AI SDK

Mastra AI

Use Lever MCP with Mastra AI

LlamaIndex

Use Lever MCP with LlamaIndex

CrewAI

Use Lever MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Ashby

Api Key

Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.

Async interview

Api Key

Async interview is an on-demand video interview platform for streamlined hiring. Candidates record responses on their schedule, so employers can review anytime.

Bamboohr

Oauth2Api Key

BambooHR is a cloud-based HR management platform for small and mid-sized businesses. It streamlines employee data, HR workflows, and reporting in one easy interface.

Breathe HR

Api Key

Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.

FAQ

Frequently asked questions

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

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

Start with Lever.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Lever tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Lever MCP with Pydantic AI

Connect Lever without auth hassles

Introduction

Also integrate Lever with

TL;DR

What is Pydantic AI?

What is the Lever MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Tool Router Session

Initialize the Pydantic AI Agent

Build the chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Lever MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Ashby

Async interview

Bamboohr

Breathe HR

Frequently asked questions

What are the differences in Tool Router MCP and Lever MCP?+

Can I use Tool Router MCP with Pydantic AI?+

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

How safe is my data with Composio Tool Router?+

Start with Lever.It takes 30 seconds.

Teams ship real agents on Composio