How to Use the Leadfeeder MCP in CrewAI

Q: How do I add Leadfeeder to my CrewAI agents?

You include the server URL in your agent's mcps list. This gives your CrewAI agents access to all nine tools, including listleads and getlead.

Q: Is it possible to limit which Leadfeeder tools CrewAI uses?

You can use the toolfilter option in your configuration. This allows you to restrict an agent to only use listleads while preventing it from accessing administrative tools like gettrackingscript.

Deploy a multi-agent sales squad using the Leadfeeder MCP Server and CrewAI.

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Connect Leadfeeder MCP to CrewAI

Create your Vinkius account to connect Leadfeeder 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 Leadfeeder with CrewAI

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Specialized agent research squads

Assign a dedicated research agent to handle your B2B intelligence. This agent uses `list_leads` to scan for new site visitors while a second analyst agent calls `get_account` to verify the company fit before flagging them for your team. This division of labor keeps your agents focused. By delegating the grunt work to a crew, you ensure that every lead is vetted before it reaches a human, saving your SDRs hours of filtering time.

Autonomous visit monitoring

Run a monitor agent that keeps watch over your site traffic. It continuously calls `list_account_visits` to detect spikes in interest and uses `get_lead` to pull context on the most active organizations. This creates a self-operating system for your sales pipeline. When the monitor detects a high-intent visitor, it passes the data to a moderator agent that drafts a personalized outreach email.

Data-driven pipeline management

Use your agents to manage your custom feeds across the organization. One agent can call `list_custom_feeds` to audit your filters, while another uses `get_custom_feed` to optimize the visitor segments based on current performance. This keeps your sales strategy aligned with actual website activity. You move from reactive prospecting to a crew that constantly refines your target list based on real-time Leadfeeder insights.

Setup guide

Set up Leadfeeder 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 Leadfeeder tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You include the server URL in your agent's `mcps` list. This gives your CrewAI agents access to all nine tools, including `list_leads` and `get_lead`.

Yes, CrewAI uses shared memory. Once one agent retrieves data via `get_account`, the rest of the crew can access that information to inform their next steps.

You can use the tool_filter option in your configuration. This allows you to restrict an agent to only use `list_leads` while preventing it from accessing administrative tools like `get_tracking_script`.

Pass your API token as an environment variable in your agent definition. The MCP server validates this token for every tool request, maintaining strict security.

They are. The server processes your private B2B firmographic data in an ephemeral sandbox. Once the agent completes its task, the transient data is cleared.

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