How to Use the Europe PMC MCP in OpenAI Agents SDK

Q: How do I connect Europe PMC to the OpenAI Agents SDK?

Pass the endpoint URL to MCPServerStreamableHttp and add it to your mcpservers list. The agent will auto-discover the search tools immediately.

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Connect Europe PMC MCP to OpenAI Agents SDK

Create your Vinkius account to connect Europe PMC 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 Europe PMC with OpenAI Agents SDK

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Query PubMed via OpenAI Agents SDK

The `search_articles` tool gives your agent direct access to Europe PMC's massive literature database. It pulls full-text papers, abstracts, and citations straight into your Python environment. You don't need to write custom REST wrappers or handle pagination logic. Your agent uses this data to answer complex biological questions with actual citations. Because OpenAI's framework includes built-in guardrails, you can restrict the agent from hallucinating references. It only quotes what the MCP server actually returns.

Track Research Grants Automatically

The `search_grants` tool lets your agent query the Grist API for funding records. You get exact award amounts, principal investigator names, and funding agency details. This connects the money to the published outcomes. Handoffs between specialized agents work perfectly here. One agent can pull the grant data, while another cross-references the resulting publications. You track the entire pipeline in the OpenAI dashboard.

Map Search Fields Dynamically

The `get_article_fields` tool exposes the exact search schema available for literature queries. Your agent reads this before building complex Boolean searches. It knows exactly which fields it can filter against. Setting `cacheToolsList=True` in your MCP Server configuration keeps this metadata snappy. The agent doesn't waste tokens guessing field names. It executes precise, structured searches every time.

Setup guide

Set up Europe PMC 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 Europe PMC tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Europe PMC. 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 Europe PMC MCP in OpenAI Agents SDK

Pass the endpoint URL to `MCPServerStreamableHttp` and add it to your `mcp_servers` list. The agent will auto-discover the search tools immediately.

Yes. The agent uses the search tools to filter by author, journal, or keyword. It builds the query strings automatically based on user prompts.

No. The SDK handles tool discovery automatically when you initialize the MCP Server. Just provide the connection parameters and start querying.

The server returns structured JSON containing titles, abstracts, DOIs, and citation counts. Your Python code parses this directly for downstream tasks.

Vinkius isolates your connection in an ephemeral V8 sandbox. The server only touches public life science publications and grant metadata. We never store your search queries or log the agent prompts.

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