How to Use the Chatwoot MCP in Google ADK

Q: Can Google ADK read all my Chatwoot contacts?

The agent triggers listchatwootcontacts to pull your customer database. It processes these records alongside any Vertex AI data you provide.

Q: How do I stop the agent from sending messages accidentally?

Use the tool filter in your setup. Exclude sendchatmessage from the exposed array so the agent can only read histories and contact info.

Feed Chatwoot histories into Gemini's massive context window using Google ADK to resolve complex support tickets.

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Connect Chatwoot MCP to Google ADK

Create your Vinkius account to connect Chatwoot to Google ADK 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 Chatwoot with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Gemini context meets Chatwoot

Support threads get messy over months of back-and-forth. Developers dump entire account histories into the Gemini token window by running `list_woot_conversations` followed by `get_chat_history`. The model digests all of it at once. It cross-references past issues with your BigQuery customer data before deciding how to handle the current ticket.

Reply directly from Google ADK

Reading data is only half the job. Once Gemini figures out the solution, it hits `send_chat_message` to push the reply straight to the customer. You do not need to build custom API wrappers for this to work. The agent figures out the right conversation ID from `get_conversation_details` and formats the text natively.

Deploy the MCP Server on Vertex

Setting this up takes three lines of Python. You wrap your Vinkius URL in `StreamableHttpServerParameters` and pass it to the MCP toolset. Drop that object into your `LlmAgent` initialization. You can even use the tool_names filter if you only want the model to read data and block it from sending messages.

Setup guide

Set up Chatwoot MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Chatwoot tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Chatwoot_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chatwoot tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Chatwoot. 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 Chatwoot MCP in Google ADK

Install the google-adk package. Configure StreamableHttpServerParameters with your MCP endpoint and attach it to your agent's tools list.

The agent triggers list_chatwoot_contacts to pull your customer database. It processes these records alongside any Vertex AI data you provide.

Use the tool filter in your setup. Exclude send_chat_message from the exposed array so the agent can only read histories and contact info.

It handles every channel you configured. The model calls list_chatwoot_inboxes to distinguish between WhatsApp, email, and web widget threads.

Vinkius handles the API transit through an ephemeral zero-trust sandbox. The contact details and message contents never touch disk storage outside your Google Cloud environment.

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