How do I get an Apollo API Key?

Log in to your Apollo.io account, go to **Settings > Integrations > API**, and generate a new API key. Ensure you have the necessary permissions based on your plan.

Does searching for people consume credits?

Basic searching typically does not consume credits, but 'enriching' a contact to reveal their verified email or phone number will consume Apollo export credits according to your subscription plan.

Can I add contacts directly to my sequences?

Yes! Use the `add_contact_to_sequence` tool. You'll need the Contact IDs, the Sequence ID, and the ID of the email address you want to use for the outreach.

Apollo.io MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Apollo.io
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Apollo.io through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Apollo.io "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Apollo.io?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Apollo.io MCP Server

The Apollo.io MCP Server provides direct access to one of the world's largest B2B databases. Connect your Apollo account to your AI agent to automate prospecting, data enrichment, and outreach workflows using natural language.

Pydantic AI validates every Apollo.io tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Targeted Prospecting — Search for people and organizations using granular filters like job titles, industries, and locations.
Data Enrichment — Instantly fill in missing details for people and companies. Get verified emails, phone numbers, and company insights.
Engagement Automation — List your sales sequences and add new contacts to them directly from your chat.
Workspace Management — Search and manage your saved contacts within your Apollo workspace.

The Apollo.io MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Apollo.io to Pydantic AI via MCP

Follow these steps to integrate the Apollo.io MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Apollo.io with type-safe schemas

Why Use Pydantic AI with the Apollo.io MCP Server

Pydantic AI provides unique advantages when paired with Apollo.io through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Apollo.io integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Apollo.io connection logic from agent behavior for testable, maintainable code

Apollo.io + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Apollo.io MCP Server delivers measurable value.

Type-safe data pipelines: query Apollo.io with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Apollo.io tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Apollo.io and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Apollo.io responses and write comprehensive agent tests

Apollo.io MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Apollo.io to Pydantic AI via MCP:

add_contact_to_sequence

Add contact to sequence

get_call

Get call details

get_contact

Get contact by ID

list_email_accounts

List connected email accounts

list_sequences

List sequences/campaigns

search_contacts

Search Apollo contacts

search_organizations

Search organizations

search_people

Search mixed people

Example Prompts for Apollo.io in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Apollo.io immediately.

"Find people with the title 'CEO' in the 'Software' industry located in San Francisco."

"Enrich the organization data for 'vinkius.com'."

"Add contact 'c_123' to my 'New Year Campaign' sequence."

Troubleshooting Apollo.io MCP Server with Pydantic AI

Common issues when connecting Apollo.io to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Apollo.io + Pydantic AI FAQ

Common questions about integrating Apollo.io MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Apollo.io MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.