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How to integrate Apollo MCP with Pydantic AI

Connect Pydantic AI to Apollo MCP. Bulk enrich profiles for new leads, add contacts to outreach sequence now, and more using natural language, with authentication handled for you.

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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.

72 Tools

Introduction

This guide walks you through connecting Apollo to Pydantic AI using the Composio tool router. By the end, you'll have a working Apollo agent that can search and enrich people and companies, manage contacts and accounts, run email sequences, track deals, and log calls and tasks through natural language commands.

This guide will help you understand how to give your Pydantic AI 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

Claude CodeCursorChatGPTClaude CoworkAntigravityOpenAI Agents SDKClaude Agent SDKGrok BotMuseCodexGrok BuildVS CodeOpenCodeOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Apollo
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Apollo workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 contacts, organizations, outreach, pipeline, conversations, and analytics, so your agent can find prospects, enrich records, manage sequence participation, update sales stages, and review performance on your behalf.

  • Prospect search and enrichment: Have your agent search for people and enrich person or organization records with data from Apollo.
  • Sequence and outreach management: Let the agent find sequences, add contacts to them, update contact participation status, and review sent outreach emails and engagement activity.
  • Contact and account updates: Direct your agent to update contact stages, account stages, and ownership assignments across your sales records.
  • Pipeline, task, and conversation research: Instruct your agent to retrieve deal details, search sales tasks, and review recorded conversations with transcripts, participants, and related opportunities.
  • Sales insights and company signals: Have your agent query analytics reports, check credit usage, find company news, and review organization job postings.

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Apollo
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Apollo
  • MCPServerStreamableHTTP connects to the Apollo MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Apollo
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["apollo"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
apollo_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[apollo_mcp],
    instructions=(
        "You are a Apollo assistant. Use Apollo tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Apollo endpoint
  • The agent uses GPT-5 to interpret user commands and perform Apollo operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Apollo.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Apollo API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Apollo
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["apollo"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    apollo_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[apollo_mcp],
        instructions=(
            "You are a Apollo assistant. Use Apollo tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Apollo.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Apollo through Composio's Tool Router. With this setup, your agent can perform real Apollo actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Apollo for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Activate Sequence

Activate an inactive Apollo sequence and begin its scheduled outreach.

Add Contacts to Sequence

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

Add People to Prospects

Save Apollo person IDs returned by APOLLO_PEOPLE_SEARCH as persistent prospect contacts.

Archive Sequence

Archive an Apollo sequence, making it inactive and finishing all enrolled contacts.

Bulk organization enrichment

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

Bulk people enrichment

Enriches up to 10 person profiles from Apollo's database; charges may apply per person enriched, and unmatched entries may be null.

Bulk update account stage

Bulk updates the stage for specified existing Apollo.

Complete Apollo Task

Requests completion of an Apollo task and returns the resulting task state.

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 Email Draft

Create an unsent Apollo outreach draft, or return the existing draft already linked to outreach_task_id.

Create Apollo Sequence

Create an Apollo outreach sequence, optionally including steps and email variants.

Create Apollo Sequence Step

Create one step at a specified position in an existing Apollo outreach sequence.

Create Apollo Task

Tool to create a single task in Apollo.

Deactivate Sequence

Deactivate an active Apollo sequence.

Export Conversations

Start an asynchronous gzipped JSON conversation export and email a team member when it is ready.

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 Conversation

Retrieve full Apollo conversation details, including transcript, participants, recordings, and opportunities.

Get Conversation Export

Retrieve the download redirect URL for a previously started Apollo conversation export.

Get Current User Profile

Return the authenticated Apollo user's identity and optional credit balances.

Get Apollo deal

Retrieves information about a specific deal by its ID.

Get Email Activities

Retrieves content, open and click activity, and recipient details for one Apollo sequence email.

Get Email Content

Retrieve content for up to 10 sent team outreach emails.

Get Labels

Retrieves all labels from Apollo.

Get opportunity stages

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

Get Organization by ID

Retrieves organization information by Apollo ID, including available funding, technology, and employee data.

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 Apollo Task

Retrieves the full details of one Apollo task by ID, including associated records and type-specific data when present.

Get typed custom fields

Retrieves all typed custom field definitions available in the Apollo.

Get Apollo User

Retrieve one teammate in the connected Apollo workspace by Apollo user ID.

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 Notes

List notes associated with Apollo records.

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

Search Apollo's organization database using filters and paginated results.

Enrich person with Apollo

Enriches a person using an Apollo ID, email, hashed email, LinkedIn URL, or first and last name with organization name or domain.

Apollo people search

Searches Apollo's database for net-new prospects using filters, returning preview records with a display limit of 50,000.

Query Analytics Report

Query Apollo analytics metrics, dimensions, filters, and date ranges.

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 Apollo Conversations

Search Apollo video meetings and dialer calls using record, participant, date, scorecard, sorting, and visibility filters.

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

Search Apollo sequences, such as automated email campaigns, optionally filtering by full or partial name.

Search tasks

Searches for tasks in Apollo.

Send Email Now

Queue an Apollo email for external sending; success means queued, not delivered.

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

Pauses or marks a contact as finished in a designated Apollo sequence.

Update Apollo deal

Updates specified fields of an existing Apollo.

Update Apollo List

Rename an Apollo list and optionally change its Book of Business status.

Update Sequence

Update an Apollo sequence's settings, ownership, sharing, steps, and touches.

Update Apollo Task

Update editable details of an existing Apollo task.

View API Usage Stats

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

View Credit Usage Stats

Read team balances by credit type for Apollo's current billing cycle.

FRAMEWORKS

How to build Apollo MCP Agent with another framework

Claude Code logo

Claude Code

Use Apollo MCP with Claude Code

Cursor logo

Cursor

Use Apollo MCP with Cursor

ChatGPT logo

ChatGPT

Use Apollo MCP with ChatGPT

Claude Cowork logo

Claude Cowork

Use Apollo MCP with Claude Cowork

Antigravity logo

Antigravity

Use Apollo MCP with Antigravity

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Apollo MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Apollo MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Apollo MCP with Grok Bot

Muse logo

Muse

Use Apollo MCP with Muse

Codex logo

Codex

Use Apollo MCP with Codex

Grok Build logo

Grok Build

Use Apollo MCP with Grok Build

VS Code logo

VS Code

Use Apollo MCP with VS Code

OpenCode logo

OpenCode

Use Apollo MCP with OpenCode

OpenClaw logo

OpenClaw

Use Apollo MCP with OpenClaw

Hermes logo

Hermes

Use Apollo MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Apollo MCP with Atomic Agent

Google ADK logo

Google ADK

Use Apollo MCP with Google ADK

LangChain logo

LangChain

Use Apollo MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Apollo MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Apollo MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Apollo MCP with LlamaIndex

CrewAI logo

CrewAI

Use Apollo MCP with CrewAI

AutoGen logo

AutoGen

Use Apollo MCP with AutoGen

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. Pydantic AI 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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