How to Use the Apollo.io MCP in CrewAI

Deploy autonomous sales teams that research and enroll Apollo.io prospects using this CrewAI MCP integration.

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Connect Apollo.io MCP to CrewAI

Create your Vinkius account to connect Apollo.io to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Apollo.io with CrewAI

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Perplexity

Specialized SDR agent teams

Stop writing monolithic scripts. Build a crew where a Researcher agent strictly uses `search_organizations` to map out target accounts. Once finished, it hands the context to a Sourcer agent that runs `search_contacts` to pinpoint the exact buyers. This division of labor prevents context limits from blowing up. Each agent only loads the specific tools it needs, keeping the reasoning sharp and focused on a single objective.

Autonomous campaign execution with CrewAI

Let your AI team handle the entire outbound motion via this MCP Server. A Manager agent reviews the sourced leads, checks available campaigns via `list_sequences`, and assigns an Executor agent to run `add_contact_to_sequence`. The process runs entirely unattended. You just define the initial prompt, and the crew coordinates the API calls, passing lead IDs and sequence parameters between their shared memory states.

Automated call analysis pipelines

Transcripts hold massive amounts of deal intelligence. Assign an Analyst agent to pull recent conversation records using `get_call`. It reads the transcripts, extracts objections, and updates your CRM notes. Setup takes seconds. Pass the Vinkius endpoint URL directly into the server array of your agent definition. For tighter control, wrap it in `MCPServerHTTP` and apply a filter so the Analyst cannot accidentally trigger a sequence.

Setup guide

Set up Apollo.io MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Apollo.io tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Apollo.io Analyst",
    goal="Access and analyze Apollo.io data via MCP.",
    backstory="Expert analyst with direct Apollo.io access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Apollo.io transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Apollo.io Analyst",
        goal="Access and analyze Apollo.io data via MCP.",
        backstory="Expert analyst with direct Apollo.io access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Apollo.io transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Apollo.io. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Apollo.io MCP in CrewAI

Install the required Python tools package. Add your Vinkius URL directly to the connection parameter when defining your specific agent.

Yes. You can provide the same MCP Server endpoint to different agents, or restrict access by assigning specific lookup tools to dedicated roles.

The Python framework natively supports stdio, SSE, and Streamable HTTP. It negotiates the best connection method with the Vinkius infrastructure automatically.

Use the HTTP wrapper and configure a tool filter. You can explicitly block `add_contact_to_sequence` while allowing read-only access to searches.

Completely. When your agent fetches raw conversational data via `get_call`, the text processes inside an ephemeral V8 sandbox. Vinkius destroys the environment immediately after the task completes.

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