How to integrate Apollo MCP with LangChain

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Introduction

This guide walks you through connecting Apollo to LangChain using the Composio tool router. By the end, you'll have a working Apollo agent that can bulk enrich profiles for new leads, add contacts to outreach sequence now, create a new sales deal for acme, list all opportunity stages in pipeline through natural language commands.

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

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Apollo project to Composio
  • Create a Tool Router MCP session for Apollo
  • Initialize an MCP client and retrieve Apollo tools
  • Build a LangChain agent that can interact with Apollo
  • 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 Apollo MCP server, and what's possible with it?

The Apollo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apollo account. It provides structured and secure access to your CRM and lead generation data, so your agent can create contacts, enrich organizations, manage deals, update account stages, and automate tasks for your sales pipeline—all on your behalf.

  • Contact and account creation: Instantly add new contacts or accounts to Apollo, linking them to organizations and stages to keep your CRM up to date with zero manual entry.
  • Bulk data enrichment: Rapidly enrich multiple people or organizations at once, leveraging Apollo's database to fill gaps and update your records with the latest information.
  • Sales opportunity and pipeline management: Let your agent create new deals, retrieve opportunity stages, and move accounts through your sales funnel to optimize pipeline performance.
  • Automated outreach sequencing: Add contacts to email sequences, making it easy to launch targeted campaigns and follow-ups without lifting a finger.
  • Task creation and label organization: Generate actionable Apollo tasks for your team and organize contacts or accounts with labels, so nothing slips through the cracks.

Supported Tools & Triggers

Tools
Add Contacts to SequenceAdds contacts to a specified apollo email sequence by initiating an asynchronous background job and returning its details.
Bulk organization enrichmentEnriches data for up to 10 organizations simultaneously by providing a list of their base company domains (e.
Bulk people enrichmentUse to enrich multiple person profiles simultaneously with comprehensive data from apollo's database.
Bulk update account stageBulk updates the stage for specified existing apollo.
Create an Apollo accountCreates a new account in apollo.
Create Apollo contactCreates a new contact in apollo.
Create Apollo dealCreates a new sales opportunity (deal) in apollo.
Create Apollo TaskCreates a distinct apollo.
Get LabelsRetrieves all labels from apollo.
Get opportunity stagesRetrieves all configured opportunity (deal) stages from the apollo.
Get Organization Job PostingsRetrieves paginated job postings for a specified organization by its id, optionally filtering by domain; ensure `organization id` is a valid identifier.
Get typed custom fieldsRetrieves all typed custom field definitions available in the apollo.
List Apollo account stagesRetrieves all available apollo.
List apollo contact stagesRetrieves all available contact stages from an apollo account, including their unique ids and names.
List Apollo dealsRetrieves a list of deals from apollo, using apollo's default sort order if 'sort by field' is omitted.
List email accountsRetrieves all email accounts and their details for the authenticated user; takes no parameters.
List Apollo UsersRetrieves a list of all users (teammates) associated with the apollo account, supporting pagination via `page` and `per page` parameters.
Enrich organization dataFetches comprehensive organization enrichment data from apollo.
Search organizations in ApolloSearches apollo's database for organizations using various filters; consumes credits (unavailable on free plans), retrieves a maximum of 50,000 records, and uses `page` (1-500) and `per page` (1-100) for pagination.
Enrich person with ApolloEnriches and retrieves information for a person from apollo.
Apollo people searchSearches apollo's contact database for people using various filters; results are limited to 50,000 records and this action does not enrich contact data.
Search Apollo AccountsSearches for accounts within your existing apollo.
Search Apollo contactsSearches apollo contacts using keywords, stage ids (from 'list contact stages' action), or sorting (max 50,000 records; `sort ascending` requires `sort by field`).
Search sequencesSearches for sequences (e.
Search tasksSearches for tasks in apollo.
Update an Apollo accountUpdates specified attributes of an existing account in apollo.
Update Apollo contactUpdates specified attributes of an existing apollo.
Update contact ownershipUpdates the ownership of specified apollo contacts to a given apollo user, who must be part of the same team.
Update contact stageUpdates the stage for one or more existing contacts in apollo.
Update contact status in sequenceUpdates a contact's status within a designated apollo sequence, but cannot set the status to 'active'.
Update Apollo dealUpdates specified fields of an existing apollo.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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 Apollo 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 Apollo tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Apollo 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 Apollo tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "apollo-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 Apollo MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Apollo 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 Apollo 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 Apollo 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=['apollo']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "apollo-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 Apollo 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 Apollo 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 Apollo MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Apollo MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Apollo MCP with Claude Agent SDK

Google ADK

Google ADK

Use Apollo MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Apollo MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Apollo MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Apollo MCP with LlamaIndex

CrewAI

CrewAI

Use Apollo MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Apollo MCP?

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

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

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

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