How to Use the Landbot MCP in AutoGen

Q: How do I configure Landbot tools in AutoGen?

Install autogen-extmcp. Pass your server URL to mcpservertools and inject the resulting list into your AssistantAgent constructor.

Q: Can AutoGen agents read Landbot customer profiles?

Yes. Any agent with access to getcustomerdetails can pull user properties to inform their debate. They can also query listlandbotcustomers for bulk analysis.

Deploy multi-agent AutoGen teams to debate and execute Landbot conversational strategies.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Landbot MCP to AutoGen

Create your Vinkius account to connect Landbot to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Landbot with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-agent debate for support escalation

The `handoff_to_agent` tool transfers a live conversation from a bot to a human operator. In AutoGen, you do not hardcode this trigger. A support agent and a cost-control agent debate whether the user's issue warrants human intervention. They check `get_customer_details` to weigh the account value against the current queue length pulled from `list_team_agents`. Only when both agents reach an agreement does the system execute the handoff. You save expensive human hours for high-complexity problems.

Autonomous WhatsApp template dispatch

The `send_whatsapp_template` tool delivers pre-formatted messages to your audience. Your AutoGen marketing agent drafts the campaign parameters while a compliance agent reviews the payload against WhatsApp's strict template rules. If the compliance agent flags a violation, the marketing agent revises the input. Once approved, the system fires the approved message. You can follow up successful deliveries by triggering specific conversational paths with `trigger_bot_flow`.

Audit your Landbot MCP Server infrastructure

The `get_account_info` tool retrieves your current API limits and subscription status. An AutoGen monitoring agent runs this check daily and cross-references it with the active configurations pulled from `list_active_bots` and `list_message_hooks`. If the system detects an impending rate limit, it alerts an operations agent to throttle incoming requests. The agents use `update_customer_field` to tag affected users automatically. You build a self-healing customer support infrastructure that requires zero manual oversight.

Setup guide

Set up Landbot MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Landbot tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Landbot_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Landbot data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Landbot_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Landbot data")
    print(result.messages[-1].content)

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Landbot now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Landbot MCP in AutoGen

Install `autogen-ext[mcp]`. Pass your server URL to `mcp_server_tools` and inject the resulting list into your `AssistantAgent` constructor.

Yes. Any agent with access to `get_customer_details` can pull user properties to inform their debate. They can also query `list_landbot_customers` for bulk analysis.

One agent decides the timing while another formats the payload for `send_proactive_text` or `send_proactive_image`. They collaborate to ensure the message fits the context.

You assign specific tools to specific agents during setup. The compliance agent gets read-only access, while the execution agent gets the write endpoints.

This server reads and writes live chat histories and contact details. Vinkius handles the authentication layer externally, meaning your AutoGen agents never touch the raw API keys. The execution environment spins down immediately after the tool call finishes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript