How to Use the Adzuna Alternative MCP in OpenAI Agents SDK

Q: How do I connect the Adzuna Alternative MCP Server to the OpenAI Agents SDK?

Install the framework via pip. Initialize MCPServerStreamableHttp with your Vinkius endpoint URL and pass it to your Agent constructor's mcpservers list. The SDK automatically discovers all eight available tools.

Q: Can the OpenAI Agents SDK cache Adzuna Alternative MCP tool definitions?

Yes. Set cacheToolsList=True during your setup. This prevents the agent from re-fetching the tool schemas on every single invocation, which speeds up your response times considerably.

Q: How does the agent know which job categories exist?

It calls the getcategories tool. This returns the exact list of employment sectors recognized by the API, so your agent constructs valid search queries instead of guessing industry names.

Build production-grade recruitment tools with OpenAI Agents SDK. Connect your AI directly to real-time labor market data.

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Connect Adzuna Alternative MCP to OpenAI Agents SDK

Create your Vinkius account to connect Adzuna Alternative 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 Adzuna Alternative with OpenAI Agents SDK

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Feed Market Data to OpenAI Agents

Your deployment needs hard facts, not model hallucinations. Connecting this MCP Server gives your agent direct access to current job postings via `search_jobs`. You pass the query parameters, and the agent pulls back structured vacancy records to feed into your broader application logic. This goes beyond basic queries. When a user asks about compensation expectations, the agent hits `get_histogram` to pull factual salary distributions. The SDK handles the tool discovery automatically, keeping your context window focused on the actual data instead of managing API endpoints.

Run Historical Salary Analytics

Tracking compensation trends requires looking backward. The `get_history` tool pulls time-series data for vacancies and pay rates across different sectors. Your agent grabs this raw data and immediately formats it for your dashboard or reporting pipeline. We built this for systems that need reliable inputs. Combine that historical view with `get_jobsworth` to generate accurate, data-backed salary estimates for specific roles. Built-in guardrails ensure the agent actually verifies these figures before presenting them to end users.

Map Regional Hiring Demand

Location dictates the job market. Using `get_geodata`, your system maps out exactly where the hiring spikes are happening right now. It returns vacancy counts broken down by specific geographic regions so you can target your recruitment efforts. You can cross-reference those regional metrics with `get_top_companies` to see who is driving the local demand. The agent pulls the top employers by vacancy count, giving you a clear picture of the competitive landscape without writing custom scraping logic.

Setup guide

Set up Adzuna Alternative 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 Adzuna Alternative tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Adzuna Alternative 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="Adzuna Alternative Agent",
            instructions="You have access to Adzuna Alternative 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 Adzuna. 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 Adzuna Alternative MCP in OpenAI Agents SDK

Install the framework via pip. Initialize `MCPServerStreamableHttp` with your Vinkius endpoint URL and pass it to your Agent constructor's `mcp_servers` list. The SDK automatically discovers all eight available tools.

Yes. Set `cacheToolsList=True` during your setup. This prevents the agent from re-fetching the tool schemas on every single invocation, which speeds up your response times considerably.

The SDK handles the error gracefully. You can configure handoffs or fallback routines within your agent system if the labor market API times out or returns an empty dataset.

It calls the `get_categories` tool. This returns the exact list of employment sectors recognized by the API, so your agent constructs valid search queries instead of guessing industry names.

Vinkius runs the MCP Server in an ephemeral V8 Isolate Sandbox. When your agent pulls salary histograms or regional vacancy counts, the server processes the request and immediately destroys the environment. Zero residual query data remains on our infrastructure.

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