How to Use the Landbot MCP in CrewAI

Q: Can CrewAI agents manage Landbot message hooks?

Your agents can query listmessagehooks to see which events are currently configured. This helps them understand how the system reacts to user activity.

Deploy autonomous agent crews in CrewAI to manage customer support, monitor bot performance, and execute conversation flows.

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Connect Landbot MCP to CrewAI

Create your Vinkius account to connect Landbot 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 Landbot with CrewAI

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Autonomous bot monitoring with CrewAI

Assign a monitor agent to watch your active flows using `list_active_bots`. It can identify underperforming sequences without human input. If an issue arises, the monitor agent triggers a secondary agent to investigate. It keeps your support operations running 24/7.

Multi-agent task execution for Landbot

Coordinate a crew where one agent gathers customer info via `list_landbot_customers` and another processes that data to update records. The agents share memory, so each step builds on the last. It removes the need for manual data entry across your support stack.

Scale support with specialized agents

Let your agents decide when to trigger specific paths using `trigger_bot_flow`. They can execute complex logic based on the user's previous interactions. This turns your conversational flows into an automated engine. The agents handle the heavy lifting while you define the strategy.

Setup guide

Set up Landbot 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 Landbot tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL into the agent's MCP configuration list. CrewAI will automatically import the tools for your agents to use.

Your agents can query `list_message_hooks` to see which events are currently configured. This helps them understand how the system reacts to user activity.

Absolutely. You can place the Landbot tools in a shared pool that both manager and worker agents access to complete tasks.

It touches user IDs, conversation properties, and custom fields you have defined in your bot flows. This is limited to what is required for agent tasks.

The server acts as a sandbox. Your agent crew only interacts with the data through the defined tools, preventing unauthorized access to your account.

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