How to integrate Lever MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Lever to the OpenAI Agents SDK 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 OpenAI Agents SDK 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

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 Lever
  • Configure an AI agent that can use Lever as a tool
  • Run a live chat session where you can ask the agent to perform Lever 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 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.

Supported Tools & Triggers

Tools
Add Opportunity LinksTool to add links to a contact associated with an opportunity.
Add Opportunity SourcesTool to add sources to an opportunity.
Add Opportunity TagsTool to add tags to an opportunity.
Create Form SubmissionTool to create a completed profile form submission for a candidate's opportunity profile.
Create Form TemplateTool to create a profile form template for an account.
Create InterviewTool to create an interview on an externally-managed panel in Lever.
Create NoteTool to create a note on an opportunity profile or add a threaded comment to an existing note.
Create OpportunityTool to create a new candidate opportunity in Lever.
Create PanelTool to create a new interview panel for an opportunity.
Create RequisitionTool to create a new requisition in Lever for tracking hiring needs.
Create Requisition FieldTool to create a custom requisition field schema for use across requisitions.
Create Requisition Field OptionTool to add new options to a dropdown requisition field without replacing existing options.
Upload FileTool to upload a file temporarily to Lever for use with posting applications.
Create UserTool to create a new user in the Lever system.
Deactivate UserTool to deactivate a user in the Lever system.
Delete Form TemplateTool to delete a profile form template from account.
Delete InterviewTool to delete an interview from an opportunity panel.
Delete NoteTool to delete a note on an opportunity.
Delete PanelTool to delete a panel from an opportunity.
Delete RequisitionTool to delete or archive a requisition from Lever account.
Delete Requisition FieldTool to delete a requisition field from the account.
Delete Requisition Field OptionTool to remove specific options from a dropdown requisition field.
Download FileTool to download a file associated with an opportunity.
Get File MetadataTool to retrieve metadata for a single file on an opportunity.
Get FormTool to retrieve a specific profile form for an opportunity.
Get Form TemplateTool to retrieve a single form template by unique identifier.
Get InterviewTool to retrieve a single interview for an opportunity.
Get NoteTool to retrieve a single note for an opportunity.
Get OpportunityTool to retrieve detailed information about a single opportunity.
Get PanelTool to retrieve a single interview panel for an opportunity.
Get RequisitionTool to retrieve detailed information about a single requisition by ID.
Get Requisition FieldTool to retrieve detailed information about a single custom requisition field by ID.
Get StageTool to retrieve detailed information about a single stage by its UUID.
Get UserTool to retrieve detailed information about a single user by their UUID.
List Opportunity FilesTool to list all files on an opportunity.
List FormsTool to list all profile forms for an opportunity.
List Form TemplatesTool to list all active form templates.
List InterviewsTool to list all interviews for an opportunity.
List NotesTool to list notes on an opportunity profile.
List OffersTool to list offers for an opportunity.
List OpportunitiesTool to list all opportunities in the hiring pipeline.
List PanelsTool to list all interview panels for an opportunity.
List PostingsTool to list all job postings including published, internal, closed, draft, pending, and rejected postings.
List ReferralsTool to list all referrals for an opportunity.
List Requisition FieldsTool to list all requisition field schemas in your Lever account with optional filtering.
List RequisitionsTool to list all requisitions with filtering and pagination.
List Opportunity ResumesTool to list all resumes for an opportunity.
List SourcesTool to list all recruitment sources in your Lever account.
List StagesTool to retrieve all pipeline stages in your Lever account.
List TagsTool to list all tags in your Lever account.
List UsersTool to retrieve all active users in your Lever account with optional filters.
Reactivate UserTool to reactivate a previously deactivated user in the Lever system.
Remove Contact Links by OpportunityTool to remove links from a contact associated with an opportunity.
Remove Opportunity SourcesTool to remove sources from an opportunity.
Remove Opportunity TagsTool to remove tags from an opportunity.
Update Form TemplateTool to update an existing profile form template.
Update InterviewTool to update an interview on an externally-managed panel.
Update NoteTool to update a note on an opportunity profile.
Update PanelTool to update an externally-managed panel for an opportunity.
Update RequisitionTool to update an existing requisition in Lever.
Update Requisition FieldTool to update an existing requisition field in Lever.
Update Requisition Field OptionTool to update existing options in a dropdown requisition field without replacing the entire field object.
Update UserTool to update an existing user in the Lever system.
Upload File to OpportunityTool to upload a file permanently to an opportunity.

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 Lever 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 Lever.

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 Lever Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["lever"]
)

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

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 Lever MCP?

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.

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 Lever tools.

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

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.

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 Lever data and credentials are handled as safely as possible.

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