How to integrate Lever MCP with OpenAI Agents SDK

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.

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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

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.

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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.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Lever project
  • Some knowledge of Python or Typescript
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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

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.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
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.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Lever
const session = await composio.create(userId as string, {
  toolkits: ['lever'],
});
const mcpUrl = 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.
8

Configure the agent

// Configure agent with MCP tool
const agent = new 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({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: '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 object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Lever operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
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 run().
  • The responses are printed to the console.
  • 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 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['lever'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new 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({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

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.
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.

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. 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.

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.

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