How to Use the Cliengo MCP in Google ADK

Q: How do I configure Cliengo tools inside Google ADK?

Initialize your MCP toolset by pointing McpToolset to your Vinkius HTTP transport URL. Pass the toolset directly into the tools parameter of your LlmAgent constructor.

Q: Can Google ADK filter which Cliengo webhooks are active?

Yes, the agent calls listcliengowebhooks to review your active endpoints. You can then use Google Cloud functions to process these webhooks as they trigger.

Q: Does Google ADK support long-context reasoning over Cliengo histories?

Yes, Gemini models can ingest massive outputs from getchathistory. The agent processes hours of conversational logs without losing track of early details.

Q: Can I run Google ADK queries on Cliengo website setups?

You run listcliengowebsites to let your agent discover where the chatbot is deployed. This helps the agent match incoming lead sources to specific marketing campaigns.

Run deep analysis on your Cliengo chat logs and leads using Google ADK with 1M+ token Gemini reasoning.

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Connect Cliengo MCP to Google ADK

Create your Vinkius account to connect Cliengo 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 Cliengo with Google ADK

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Analyze long-form chat logs with Google ADK

`get_contact_messages` extracts the full backlog of text exchanged with any specific lead on your website. This tool feeds raw conversational data directly into your Gemini model's context window. Because Google ADK supports million-token context lengths, you can analyze years of chat history at once. The agent identifies recurring product complaints and maps them directly to your BigQuery data warehouse.

Sync Cliengo lead records via Google ADK

`list_cliengo_leads` grabs all contact details, names, and interaction histories captured by your active chatbots. This tool serves as the primary data bridge between your site visitors and your cloud database. Your Google ADK agent pulls this list to run batch updates or search for duplicate records. You can instantly run matching queries against your existing Vertex AI customer tables without manual exports.

Expose specific tools to your Google ADK MCP Server

`list_cliengo_users` retrieves your internal team list, letting your agent know which support reps are currently active. This MCP tool allows the system to assign leads to real people based on current capacity. You configure the Google ADK `McpToolset` with a custom tool filter to limit what the agent can see. This keeps your internal user directory secure while still letting the agent read public website configurations.

Setup guide

Set up Cliengo 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 Cliengo 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="Cliengo_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Cliengo 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 Cliengo. 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 Cliengo MCP in Google ADK

Initialize your MCP toolset by pointing `McpToolset` to your Vinkius HTTP transport URL. Pass the toolset directly into the `tools` parameter of your `LlmAgent` constructor.

Yes, the agent calls `list_cliengo_webhooks` to review your active endpoints. You can then use Google Cloud functions to process these webhooks as they trigger.

Yes, Gemini models can ingest massive outputs from `get_chat_history`. The agent processes hours of conversational logs without losing track of early details.

You run `list_cliengo_websites` to let your agent discover where the chatbot is deployed. This helps the agent match incoming lead sources to specific marketing campaigns.

All contact messages and lead details are processed in an ephemeral sandbox. No data is stored on Vinkius servers, keeping your customer records compliant with enterprise security standards.

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