How to Use the Qualified.io MCP in OpenAI Agents SDK

Q: How does the Qualified.io toolset handle hiring loops inside the OpenAI Agents SDK?

You can use invitecandidatesviacohort to batch invite hundreds of candidates at once. The OpenAI Agents SDK manages these tool calls asynchronously, preventing rate limits from choking your hiring funnel.

Build production-grade OpenAI Agents SDK workflows that automatically trigger Qualified.io coding tests and review candidate submissions.

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…and any MCP-compatible client

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Connect Qualified.io MCP to OpenAI Agents SDK

Create your Vinkius account to connect Qualified.io to OpenAI Agents SDK — 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 OpenAI Agents SDK

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Trigger tests directly from OpenAI Agents SDK

Stop wasting hours setting up coding tests manually in your OpenAI Agents SDK pipeline. Let your agent run the entire Qualified.io screening workflow by triggering `invite_candidates` or `invite_candidates_via_cohort` when a resume hits your database. If an engineering applicant needs a retake, your OpenAI Agents SDK agent can instantly execute `schedule_retry_assessment_result` or terminate the test with `terminate_assessment_result`. This MCP Server integration removes the manual friction from your technical recruiting loop.

Review candidate code submissions

When a developer finishes their Qualified.io test, your OpenAI Agents SDK agent pulls down the raw code submissions using `get_assessment_result` or `get_assessment_result_exhibit`. It evaluates their code against your team's style guide and posts a structured scorecard. The OpenAI Agents SDK agent then writes its technical findings back to the candidate's profile using `create_assessment_result_review` or `update_assessment_result_review`. This keeps your entire engineering feedback loop contained inside a secure, automated pipeline.

Manage test suites dynamically via MCP

Keep your Qualified.io challenge library fresh without logging into a web UI by letting your OpenAI Agents SDK agent query active coding challenges with `list_challenges` and build custom tests on the fly using `create_assessment`. To keep candidates from leaking test questions, your OpenAI Agents SDK agent can swap out compromised challenges, call `publish_assessment`, and clean up old ones with `archive_assessment`.

Setup guide

Set up Qualified.io MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Qualified.io tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Qualified.io tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Qualified.io tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Qualified.io Agent",
            instructions="You have access to Qualified.io tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 OpenAI Agents SDK

Install openai-agents via pip, then initialize the server stream using MCPServerStreamableHttp pointing to your Vinkius Qualified.io endpoint. Pass this server instance in the mcp_servers list when instantiating your Agent object to auto-discover all 20 tools.

Yes, your OpenAI Agents SDK agent can monitor incoming webhook data, check the score with get_assessment_result, and call schedule_retry_assessment_result if a candidate encountered a technical glitch during their session.

You can use invite_candidates_via_cohort to batch invite hundreds of candidates at once. The OpenAI Agents SDK manages these tool calls asynchronously, preventing rate limits from choking your hiring funnel.

Yes, you can configure tool access policies on Vinkius or filter the tools during agent initialization to ensure your OpenAI Agents SDK agent cannot run destructive commands like unpublish_assessment or archive_assessment.

Candidate code submissions and test scores are processed securely. Vinkius operates a zero-trust, ephemeral V8 sandbox, meaning candidate data is never persisted on our servers or used to train OpenAI models.

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