How to integrate Lever MCP with LangChain

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Lever logo
LangChain logo
divider

Introduction

This guide walks you through connecting Lever to LangChain 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 LangChain 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
  • Connect your Lever project to Composio
  • Create a Tool Router MCP session for Lever
  • Initialize an MCP client and retrieve Lever tools
  • Build a LangChain agent that can interact with Lever
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Lever functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Lever tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Lever
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['lever']
)

url = session.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
  • This approach allows the agent to dynamically load and use Lever tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "lever-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Lever MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Lever tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Lever related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Lever and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['lever']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "lever-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Lever related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Lever through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Lever MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Lever MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Lever MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Lever MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Lever MCP with Claude Cowork

Codex logo

Codex

Use Lever MCP with Codex

OpenClaw logo

OpenClaw

Use Lever MCP with OpenClaw

Hermes logo

Hermes

Use Lever MCP with Hermes

CLI logo

CLI

Use Lever MCP with CLI

Google ADK logo

Google ADK

Use Lever MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Lever MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Lever MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Lever MCP with LlamaIndex

CrewAI logo

CrewAI

Use Lever MCP with CrewAI

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 LangChain?

Yes, you can. LangChain 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.

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗