How to Use the Chaport MCP in Google ADK

Q: How do I connect Chaport to Google ADK?

Use the McpToolset class in your code. Point it at the server URL, and your agent gains access to all eight tools.

Q: Can Google ADK agents filter specific Chaport tools?

You can pass a toolnames filter to the toolset. This limits the agent to only the functions you want it to perform.

Deploy Google ADK agents that query live visitor data and manage messaging queues.

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Connect Chaport MCP to Google ADK

Create your Vinkius account to connect Chaport 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 Chaport with Google ADK

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Sync Chaport messaging for Google ADK

Fetch historical logs with `get_chat_history`. Your Google ADK agent parses these sessions to maintain long-context awareness of the customer. Respond by invoking `send_agent_message`. This keeps the conversation moving within the Google Cloud environment.

Monitor your team using this MCP Server

Run `list_chaport_operators` to generate a report on current staffing. The `list_online_agents` tool provides a snapshot of who is ready to take a call. Google ADK models use this data to decide if they should escalate a query. It prevents dead-end chats by checking human availability first.

Analyze visitors via Google ADK

Query `list_website_visitors` to see current traffic. Use `get_visitor_details` to fetch specific profile attributes for your analytics pipeline. Your agent uses these outputs to feed BigQuery datasets. It turns raw visitor information into actionable business intelligence.

Setup guide

Set up Chaport 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 Chaport 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="Chaport_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chaport tools via MCP.",
    tools=mcp_tools,
)

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Why Choose Vinkius

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Common questions about Chaport MCP in Google ADK

Use the `McpToolset` class in your code. Point it at the server URL, and your agent gains access to all eight tools.

You can pass a tool_names filter to the toolset. This limits the agent to only the functions you want it to perform.

Yes. It handles both Stdio and HTTP transports. You choose the one that fits your infrastructure setup.

Absolutely. You can feed large chunks of chat history into Gemini models for deep reasoning about customer needs.

The server runs in an ephemeral sandbox. It only processes visitor names and chat content during the active request.

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

Mastra AI sdk-typescript

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