How to Use the Join MCP in OpenAI Agents SDK

Q: Can Join run autonomous screening with OpenAI Agents SDK?

Yes. The agent uses listapplications to find new candidates and evaluates them based on data from getjob.

Q: Does the Join MCP Server support multi-agent handoffs in OpenAI Agents SDK?

Absolutely. You can have one agent run listjobs to find open roles, then hand off to a vetting agent that calls getcandidate.

Build production-ready recruiting agents with OpenAI Agents SDK and this MCP Server to safely query candidate pipelines.

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Connect Join MCP to OpenAI Agents SDK

Create your Vinkius account to connect Join to OpenAI Agents SDK 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 Join with OpenAI Agents SDK

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Match applicants to jobs using OpenAI Agents SDK

Your agent reads your active job listings with `list_jobs` and grabs candidate applications using `list_applications`. It compares candidate profiles directly to the job requirements without you writing custom matching code. The agent uses `get_candidate` to pull specific resumes and work history. It evaluates the data against the open role details retrieved by `get_job` to flag top matches instantly.

Secure candidate vetting with built-in guardrails

Run background checks or interview prep steps using `get_application` to pull notes and status. The OpenAI Agents SDK applies safety constraints to ensure your agent never leaks internal recruiter notes. It validates every call to `get_me` to verify user permissions before exposing recruiting data. This setup stops the agent from executing unauthorized actions during autonomous workflows.

Map hiring teams with this specialized MCP Server

The agent coordinates hiring managers by running `list_users` to see who owns which open role. It matches these users to departments fetched via `list_departments` to route applicants correctly. By using `list_locations`, the agent filters candidates based on where they actually want to work. This keeps your hiring pipeline clean and ensures routing decisions stay accurate.

Setup guide

Set up Join 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 Join tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Join 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="Join Agent",
            instructions="You have access to Join tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Join MCP in OpenAI Agents SDK

Install the package and pass the server URL to the HTTP streamable server parameter. Your agents will auto-discover all MCP tools instantly.

Yes. The agent uses `list_applications` to find new candidates and evaluates them based on data from `get_job`.

Absolutely. You can have one agent run `list_jobs` to find open roles, then hand off to a vetting agent that calls `get_candidate`.

Set the tool list caching parameter to true. This keeps your agent fast while ensuring it always has access to the latest candidate tools.

Your candidate profiles and internal notes never train public models. The connection runs through a secure sandbox that keeps your recruiting data private.

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