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AeroLeads MCP Server for CrewAIGive CrewAI instant access to 12 tools to Add New Lead, Delete Lead, Find Email By Name, and more

Built by Vinkius GDPR 12 Tools Framework

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

Ask AI about this App Connector for CrewAI

The AeroLeads app connector for CrewAI is a standout in the Sales Automation category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
from crewai import Agent, Task, Crew

agent = Agent(
    role="AeroLeads Specialist",
    goal="Help users interact with AeroLeads effectively",
    backstory=(
        "You are an expert at leveraging AeroLeads 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 AeroLeads "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
AeroLeads
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 AeroLeads MCP Server

Connect your AeroLeads account to any AI agent and take full control of your B2B lead generation and high-fidelity contact enrichment workflows through natural conversation.

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

  • Verified Email Orchestration — Instantly find professional email addresses using prospect names and company domains with high-fidelity verification status
  • LinkedIn Enrichment Intelligence — Programmatically retrieve over 60 data points from LinkedIn URLs, including verified phone numbers, job roles, and skills
  • Prospect Lifecycle Management — List and manage your captured leads programmatically, or create new high-fidelity records directly through your agent
  • Domain Discovery Architecture — Find all professional contacts associated with a specific company domain to identify key decision-makers programmatically
  • Operational Monitoring — Track your remaining account credits and monitor team activity directly through your agent for instant performance reporting

The AeroLeads MCP Server exposes 12 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.

All 12 AeroLeads tools available for CrewAI

When CrewAI connects to AeroLeads through Vinkius, your AI agent gets direct access to every tool listed below — spanning b2b-prospecting, email-verification, lead-enrichment, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_new_lead

Manually add lead

delete_lead

Remove captured lead

find_email_by_name

Find email by name

get_account_info

Get profile info

get_credit_balance

Get credit status

get_lead_details

Get full lead info

get_linkedin_details

Enrich LinkedIn profile

list_captured_leads

List your leads

list_prospecting_lists

List lead lists

list_team_members

List account users

list_webhooks

List active webhooks

search_domain_leads

Find leads in domain

Connect AeroLeads to CrewAI via MCP

Follow these steps to wire AeroLeads into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from AeroLeads

Why Use CrewAI with the AeroLeads MCP Server

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

01

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

02

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

03

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

04

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

AeroLeads + CrewAI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for AeroLeads in CrewAI

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

01

"Find the email for 'Elon Musk' at 'tesla.com'."

02

"Enrich the profile for this LinkedIn URL: 'https://linkedin.com/in/example'."

03

"Search for all leads in the 'vinkius.com' domain."

Troubleshooting AeroLeads MCP Server with CrewAI

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

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

AeroLeads + CrewAI FAQ

Common questions about integrating AeroLeads MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.