How to Use the CHATFLY MCP in Google ADK

Q: Can Google ADK filter which CHATFLY tools the agent sees?

Yes. Provide a toolnames list to your McpToolset to expose only specific actions, like getchatbotdetails, while hiding destructive tools.

Q: How does my Google ADK agent test a CHATFLY bot?

The agent formulates a test query and fires it via sendbotmessage. It then evaluates the bot's response against your internal support guidelines.

Connect Gemini's massive context window to your CHATFLY support data using Google ADK to analyze thousands of conversations.

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Connect CHATFLY MCP to Google ADK

Create your Vinkius account to connect CHATFLY 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 CHATFLY with Google ADK

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Process entire conversation histories

Gemini models process massive CHATFLY conversation histories with ease. When you connect this MCP Server, your Google ADK agent can dump thousands of support threads into its massive context window. It starts by grabbing recent interactions through `list_fly_conversations`. From there, the agent loops through `get_conversation_history` to pull the raw text of every single chat. You can then pipe that massive block of customer feedback directly into BigQuery for sentiment analysis or product team reviews.

Google ADK chatbot management via MCP Server

Enterprise support systems require strict oversight of active chatbots. Your Gemini agent checks your current infrastructure footprint by running `get_chatfly_account_info`. It then audits every active endpoint using `list_chatfly_bots` to ensure no rogue bots are talking to customers. If a bot needs an update, the agent inspects the current training materials via `list_uploaded_documents`. You can restrict which tools the agent actually sees by passing a tool_names filter to your McpToolset configuration.

Automated bot testing and training

Automated bot testing and training keeps your support quality high. A scheduled Gemini agent can review yesterday's escalated tickets, draft new responses, and test them against your active bots using `send_bot_message`. Once the agent confirms the new answers work, it can initiate a model update by calling `trigger_bot_training`. The entire loop runs autonomously on Google Cloud, keeping your CHATFLY bots sharp without human intervention.

Setup guide

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

Install google-adk and create an McpToolset using your Vinkius HTTP endpoint URL. Pass that toolset directly to your LlmAgent tools array.

Yes. Provide a tool_names list to your McpToolset to expose only specific actions, like `get_chatbot_details`, while hiding destructive tools.

The agent formulates a test query and fires it via `send_bot_message`. It then evaluates the bot's response against your internal support guidelines.

The server itself just fetches the data. Your Google ADK agent handles the routing, meaning it can pull data via `list_uploaded_documents` and immediately write those records into your BigQuery tables.

The tools access sensitive support transcripts and uploaded knowledge base files. Vinkius relies on ephemeral, zero-trust architecture, meaning your endpoint token authenticates the request and the container vanishes immediately after execution.

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