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 CrewAI 8 tools — connect in under 2 minutes

Name: Apollo.io
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Apollo.io through Vinkius, pass the Edge URL in the `mcps` parameter and every Apollo.io tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Apollo.io Specialist",
    goal="Help users interact with Apollo.io effectively",
    backstory=(
        "You are an expert at leveraging Apollo.io tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Apollo.io "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Apollo.io becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Apollo.io tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Apollo.io

Why Use CrewAI with the Apollo.io MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Apollo.io through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Apollo.io + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Apollo.io for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Apollo.io, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Apollo.io tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Apollo.io against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Apollo.io MCP Tools for CrewAI (8)

These 8 tools become available when you connect Apollo.io to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Apollo.io + CrewAI FAQ

Common questions about integrating Apollo.io MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.