How do I find my PhantomBuster API Key?

In your PhantomBuster account, click on your name in the top right, go to **Org settings** or **Workspace settings**, and look for the **API Key** section.

Can I provide arguments when launching a Phantom?

Yes! The `launch_phantom` action accepts an optional `argument` field where you can provide a JSON string of parameters to override the default Phantom configuration.

How do I see the data extracted by a Phantom?

Use the `get_phantom_output` tool with the specific agent ID. It will return the results of the last successful execution of that Phantom.

PhantomBuster MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: PhantomBuster
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to PhantomBuster through Vinkius, pass the Edge URL in the `mcps` parameter and every PhantomBuster 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="PhantomBuster Specialist",
    goal="Help users interact with PhantomBuster effectively",
    backstory=(
        "You are an expert at leveraging PhantomBuster 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 PhantomBuster "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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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 PhantomBuster MCP Server

Connect your PhantomBuster account to any AI agent and take full control of your lead generation and web automation workflows through natural conversation.

When paired with CrewAI, PhantomBuster becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call PhantomBuster 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

Agent Oversight — List all your Phantoms and workflows to maintain visibility over your automation suite.
Automation Control — Launch and abort Phantoms directly through the agent, including support for custom arguments.
Result Retrieval — Fetch the latest outputs and data extracted by your Phantoms for immediate analysis.
Configuration Auditing — Review the setup and arguments of any Phantom to verify your automation logic.
Usage Monitoring — Get account settings and usage info to track your available execution time.

The PhantomBuster MCP Server exposes 10 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 PhantomBuster to CrewAI via MCP

Follow these steps to integrate the PhantomBuster 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 10 tools from PhantomBuster

Why Use CrewAI with the PhantomBuster MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with PhantomBuster 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

PhantomBuster + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries PhantomBuster 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 PhantomBuster, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain PhantomBuster 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 PhantomBuster against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

PhantomBuster MCP Tools for CrewAI (10)

These 10 tools become available when you connect PhantomBuster to CrewAI via MCP:

abort_phantom

Stop a running Phantom

get_phantom

Get details for a specific Phantom

get_phantom_output

Get output/results from a Phantom

get_phantom_setup

Get configuration arguments for a Phantom

get_phantombuster_account

Get account settings and usage info

get_workflow

Get details for a specific workflow

launch_phantom

Start a Phantom execution

list_containers

List all Phantom containers

list_phantoms

List all Phantom agents

list_workflows

List all automation workflows

Example Prompts for PhantomBuster in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with PhantomBuster immediately.

"List all Phantoms in my account and show their current status."

"Launch the 'LinkedIn Search Export' Phantom with ID '12345'."

"Show me the extracted data from the last run of Phantom 12345."

Troubleshooting PhantomBuster MCP Server with CrewAI

Common issues when connecting PhantomBuster 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.

PhantomBuster + CrewAI FAQ

Common questions about integrating PhantomBuster 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.