How to integrate Apollo MCP with Autogen

This guide walks you through connecting Apollo to AutoGen 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 through natural language commands. This guide will help you understand how to give your AutoGen 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.

Apollo logoApollo
Api Key

Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.

48 Tools

Introduction

This guide walks you through connecting Apollo to AutoGen 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 through natural language commands.

This guide will help you understand how to give your AutoGen 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.

Also integrate Apollo with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Apollo
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Apollo tools
  • Run a live chat loop where you ask the agent to perform Apollo operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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.

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Apollo account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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
  • 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.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Apollo via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Apollo connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Apollo session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["apollo"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Apollo tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Apollo assistant agent with MCP tools
    agent = AssistantAgent(
        name="apollo_assistant",
        description="An AI assistant that helps with Apollo operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Apollo tools from the workbench
8

Run the interactive chat loop

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

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Apollo tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Apollo and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Apollo session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["apollo"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Apollo assistant agent with MCP tools
        agent = AssistantAgent(
            name="apollo_assistant",
            description="An AI assistant that helps with Apollo operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Apollo through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Apollo, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Apollo action and event your agent gets out of the box.

Add Contacts to Sequence

Adds contacts to a specified Apollo email sequence and returns the contact details.

Bulk organization enrichment

Enriches data for up to 10 organizations simultaneously by providing a list of their base company domains (e.

Bulk people enrichment

Use to enrich multiple person profiles simultaneously with comprehensive data from Apollo's database.

Bulk update account stage

Bulk updates the stage for specified existing Apollo.

Create an Apollo account

Creates a new account in Apollo.

Bulk create Apollo accounts

Creates multiple accounts in Apollo.

Bulk create Apollo contacts

Tool to bulk create multiple contacts in Apollo with a single API call.

Create call record in Apollo

Tool to log call records in Apollo from external systems.

Create Apollo contact

Creates a new contact in Apollo.

Create custom field

Creates a new custom field in Apollo.

Create Apollo deal

Creates a new sales opportunity (deal) in Apollo.

Create Apollo Task

Tool to create a single task in Apollo.

Get Account by ID

Tool to retrieve detailed information about a specific account by its Apollo ID.

Check Apollo API key status

Tool to check whether the provided Apollo API key is valid and accepted by Apollo (health/auth check).

Get Apollo Contact

Retrieves detailed information about a specific contact by its ID.

Get Apollo deal

Retrieves information about a specific deal by its ID.

Get Labels

Retrieves all labels from Apollo.

Get opportunity stages

Retrieves all configured opportunity (deal) stages from the Apollo.

Get Organization by ID

Retrieves complete information about a specific organization by its Apollo ID.

Get Organization Job Postings

Retrieves paginated job postings for a specified organization by its ID, optionally filtering by domain; ensure `organization_id` is a valid identifier.

Get typed custom fields

Retrieves all typed custom field definitions available in the Apollo.

List Apollo account stages

Retrieves the IDs for all available account stages in your team's Apollo account.

List apollo contact stages

Retrieves all available contact stages from an Apollo account, including their unique IDs and names.

List Apollo deals

Retrieves a list of deals from Apollo, using Apollo's default sort order if 'sort_by_field' is omitted.

List email accounts

Retrieves all email accounts and their details for the authenticated user; takes no parameters.

List Fields

Retrieves all field definitions from Apollo.

List Apollo Users

Retrieves a list of all users (teammates) associated with the Apollo account, supporting pagination via `page` and `per_page` parameters.

Enrich organization data

Fetches comprehensive organization enrichment data from Apollo.

Search organizations in Apollo

Searches Apollo's database for organizations using various filters; consumes credits on every call (unavailable on free plans) — avoid re-running identical queries and surface quota errors rather than retrying.

Enrich person with Apollo

Enriches and retrieves information for a person from Apollo.

Apollo people search

Searches Apollo's contact database for people using various filters; results capped at 50,000 records and does not enrich contact data.

Search Apollo Accounts

Searches for accounts within your existing Apollo.

Search for Calls

Searches for call records in Apollo.

Search Apollo contacts

Searches Apollo contacts using keywords, stage IDs (from 'List Contact Stages' action), or sorting (max 50,000 records; `sort_ascending` requires `sort_by_field`).

Search news articles

Tool to search for news articles about companies in Apollo's database.

Search outreach emails

Tool to search for outreach emails sent through Apollo sequences.

Search sequences

Searches for sequences (e.

Search tasks

Searches for tasks in Apollo.

Update an Apollo account

Updates specified attributes of an existing account in Apollo.

Update account ownership

Updates the ownership of multiple Apollo accounts to a specified user.

Update Apollo call record

Tool to update an existing call record in Apollo.

Update Apollo contact details

Tool to update an existing contact's information in Apollo.

Update contact ownership

Updates the ownership of specified Apollo contacts to a given Apollo user, who must be part of the same team.

Bulk update Apollo contacts

Tool to bulk update multiple Apollo contacts with a single API call.

Update contact stage

Updates the stage for one or more existing contacts in Apollo.

Update contact status in sequence

Updates a contact's status within a designated Apollo sequence, but cannot set the status to 'active'.

Update Apollo deal

Updates specified fields of an existing Apollo.

View API Usage Stats

Fetches Apollo API usage statistics and rate limits for the connected team.

FAQ

Frequently asked questions

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.

Yes, you can. Autogen 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.

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.

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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