How do I authenticate?

Grab the main API Access Integration token located centrally in settings inside Landbot App context.

Can I route chats to human agents?

Yes, standard endpoints enable you to extract active sessions and invoke assignment APIs gracefully.

Do bots answer incoming queries automatically?

No interruption occurs. Read functionalities passively pull context without disconnecting current funnels.

Landbot MCP Server for Google ADK 8 tools — connect in under 2 minutes

Name: Landbot
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 8 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Landbot as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="landbot_agent",
    instruction=(
        "You help users interact with Landbot "
        "using 8 available tools."
    ),
    tools=[mcp_tools],
)

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 Landbot MCP Server

Engage your conversational pipelines through Landbot instantly using your AI assistant. Route leads, send custom programmatic messages to open channels, or check active interactions without checking external software tools.

Google ADK natively supports Landbot as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Bot Management: Oversee and pull active bot matrices.
Customer Operations: Send automated text messages securely to connected accounts.
Lead Routing: Reassign critical pipeline threads directly to live agents programmatically.

The Landbot MCP Server exposes 8 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Landbot to Google ADK via MCP

Follow these steps to integrate the Landbot MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 8 tools from Landbot via MCP

Why Use Google ADK with the Landbot MCP Server

Google ADK provides unique advantages when paired with Landbot through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Landbot

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Landbot tools with BigQuery, Vertex AI, and Cloud Functions

Landbot + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Landbot MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Landbot and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Landbot tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Landbot regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Landbot

Landbot MCP Tools for Google ADK (8)

These 8 tools become available when you connect Landbot to Google ADK via MCP:

assign_agent

Route conversation from bot to live agent status

get_bot

Get a single bot details by ID

get_customer

Retrieve specific metadata of one customer

get_messages

Fetch the chat sequence messages for a given customer context

list_bots

List all accessible bots in Landbot

list_customers

List recent customers interacting with bots

search_customers

Search for a particular customer by email

send_text_message

Send a message programmatically to a customer conversation

Example Prompts for Landbot in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Landbot immediately.

"List standard bots running active pipelines right now."

"Fetch the entire transcription log for customer ID 98453."

"Force assign the highest severity angry customer ticket to Agent Sarah."

Troubleshooting Landbot MCP Server with Google ADK

Common issues when connecting Landbot to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Landbot + Google ADK FAQ

Common questions about integrating Landbot MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.