How to Use the Insightful MCP in Google ADK

Q: How do I register the Insightful tools in my Google ADK agent?

Instantiate McpToolset with your Vinkius MCP HTTP URL. Pass that toolset directly into the tools list of your LlmAgent in your Python setup.

Q: Can my Google ADK agent combine Insightful data with BigQuery database tables?

Absolutely. Your agent can pull attendance records via getattendance and run SQL queries in BigQuery to correlate active hours with your internal financial models.

Feed live Insightful productivity metrics directly into your Gemini-powered enterprise Google ADK agents.

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Connect Insightful MCP to Google ADK

Create your Vinkius account to connect Insightful 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 Insightful with Google ADK

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Track regional team structures with this MCP Server.

This MCP Server uses `list_locations` to let your Gemini agent map where your physical and remote teams operate. The agent combines this geographic data with `list_teams` to build a complete organizational chart in its context window. Your Google ADK agent processes these complex regional hierarchies within Gemini's massive one-million-token context window. This makes it easy to analyze multi-city operations without running out of memory.

Analyze employee performance inside Google ADK.

The `get_productivity` tool delivers clean, aggregated performance metrics straight to your Gemini reasoning loop. Your agent uses `get_employee` to map these metrics back to specific worker profiles, ensuring individual performance reviews are backed by actual data. You can feed this structured data directly into BigQuery for long-term historical analysis. The Google ADK makes it simple to move your real-time productivity metrics from the API into your enterprise data warehouse.

Monitor project progress automatically.

The `list_projects` tool fetches your entire project registry so your agent can track active initiatives. By querying `list_tasks`, the agent identifies which specific assignments are blocking your timeline. If a project stalls, your agent can trigger external alerts using the endpoints managed via `list_webhooks`. This keeps your project management pipeline moving without requiring manual dashboard checks.

Setup guide

Set up Insightful 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 Insightful 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="Insightful_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Insightful 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 Insightful. 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.

Why Choose Vinkius

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Common questions about Insightful MCP in Google ADK

Instantiate `McpToolset` with your Vinkius MCP HTTP URL. Pass that toolset directly into the tools list of your `LlmAgent` in your Python setup.

Yes, you can use the optional tool name filter when defining your toolset. This prevents the agent from seeing administrative tools like `list_webhooks` if it only needs productivity data.

Gemini's long-context window easily processes thousands of logs returned by `list_activity`. The ADK parses the JSON response and feeds it directly into the model's reasoning space.

Absolutely. Your agent can pull attendance records via `get_attendance` and run SQL queries in BigQuery to correlate active hours with your internal financial models.

Your employee activity logs and productivity metrics are processed entirely through secure Google Cloud infrastructure. Vinkius handles the MCP server API tokens using zero-trust protocols, ensuring no raw data is exposed to unauthorized networks.

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