How to Use the Qualified.io MCP in Google ADK

Analyze technical candidate performance at enterprise scale by connecting Google ADK agents to your Qualified.io assessment data.

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Connect Qualified.io MCP to Google ADK

Create your Vinkius account to connect Qualified.io to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Qualified.io with Google ADK

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Run high-volume hiring inside Google ADK

Enterprise hiring demands scale, which is why your Google ADK agent can cross-reference candidate profiles in BigQuery and trigger targeted Qualified.io tests using `invite_candidates_via_cohort` or `invite_candidates`. The Google ADK agent tracks the entire candidate journey, calling `cancel_invitation` or `terminate_assessment_result` to clean up active pipelines and free up assessment licenses when candidates drop out.

Extract deep evaluation insights

Feed raw Qualified.io code submissions directly into your analysis pipeline by letting your Google ADK agent fetch full test metrics using `get_assessment_result` or `get_assessment_result_exhibit`. Once the evaluation is complete, the Google ADK agent can create formal scorecards using `create_assessment_result_review` to run predictive hiring models that map test scores directly to on-the-job engineering success.

Manage challenges with Google ADK

Prevent test cheating by letting your Google ADK agent scan your Qualified.io library using `list_challenges` and `get_challenge`, then assemble unique assessments on the fly with `create_assessment`. The Google ADK agent can instantly update your active catalog using `publish_assessment` or `unpublish_assessment` to ensure candidates always receive fresh coding challenges.

Setup guide

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

Use McpToolset with your Vinkius HTTP endpoint parameter inside your Python script. Pass the toolset directly to your Google ADK LlmAgent to let Gemini models interact with your candidate assessment suite.

Yes, Gemini's million-token context window allows the Google ADK agent to ingest massive candidate codebases retrieved via get_assessment_result_exhibit and perform deep, multi-file code reviews.

Your Google ADK agent can monitor application updates in Vertex AI, match candidates to specific technical roles, and automatically dispatch Qualified.io assessment links using invite_candidates.

Yes, you can use the optional tool name filters in the McpToolset configuration to expose only read tools like list_assessment_results and block write actions.

Your candidate assessment scores and personal details are processed through secure, ephemeral V8 sandboxes on Vinkius. No candidate code or email data is ever stored permanently on the proxy or used for public model training.

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