How to Use the Findymail MCP in CrewAI

Q: Can one CrewAI agent search leads while another verifies them with Findymail?

Yes, that is the recommended pattern. Assign searchleads to your research agent and verifyemail to your validation agent to create a highly efficient pipeline.

Q: How do CrewAI agents handle credit limits on Findymail?

You can assign a monitoring agent to run getcreditssummary before starting a run. If the balance is too low, the monitor agent can halt the crew to prevent incomplete runs.

Deploy specialized agent teams in CrewAI using this MCP Server to autonomously build, verify, and clean your B2B prospect lists.

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Connect Findymail MCP to CrewAI

Create your Vinkius account to connect Findymail 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 Findymail with CrewAI

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Multi-agent lead generation with CrewAI and Findymail

`search_leads` gives your researcher agent the power to scan industries and pull raw prospect profiles. This tool operates as the first step in a multi-agent assembly line. In an MCP-powered CrewAI setup, the researcher agent hands these raw profiles to an analyst agent. This division of labor keeps your operations focused and prevents single-agent fatigue.

Autonomous email validation and list management

`verify_email` ensures your sender reputation remains intact by weeding out bad addresses before they hit your CRM. This MCP tool is typically assigned to a specialized QA agent in your crew. The QA agent runs every found address through the verification engine. Once cleared, the agent uses `create_contact_list` to group the clean leads into targeted outreach segments.

Deep company enrichment for personalized outreach

`enrich_company` gathers firmographic details to help your copywriting agent write personalized cold emails. This tool pulls employee counts, funding data, and industry classifications. Armed with this data, your crew can customize templates based on actual company metrics. This transforms generic outreach into highly targeted messages that actually get replies.

Setup guide

Set up Findymail 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 Findymail tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Findymail 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="Findymail Analyst",
        goal="Access and analyze Findymail data via MCP.",
        backstory="Expert analyst with direct Findymail access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Findymail 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 Findymail. 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 Findymail MCP in CrewAI

Install the crewai package and pass your Vinkius HTTP endpoint directly into the mcps list of your Agent. The agent automatically discovers tools like `find_email` and `verify_email`.

Yes, that is the recommended pattern. Assign `search_leads` to your research agent and `verify_email` to your validation agent to create a highly efficient pipeline.

You can assign a monitoring agent to run `get_credits_summary` before starting a run. If the balance is too low, the monitor agent can halt the crew to prevent incomplete runs.

Yes, CrewAI supports stdio, SSE, and HTTP transports. Vinkius hosts the MCP Server on secure HTTP, making integration as simple as passing a URL to your crew configuration.

All corporate emails and phone numbers processed by the server are handled in isolated, ephemeral sandboxes. Vinkius ensures zero-trust execution, so no business data is ever cached or exposed.

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