How to Use the EBI InterPro MCP in OpenAI Agents SDK

Q: How do I register the EBI InterPro MCP Server tools with the OpenAI Agents SDK?

You register the server by passing an MCPServerStreamableHttp instance directly into your agent configuration. Run pip install openai-agents first, point the server URL to your Vinkius endpoint, and set mcpservers=server in your agent initialization.

Q: Can my OpenAI Agents SDK pipeline perform parallel domain searches in EBI InterPro?

Yes, your agents run concurrent lookups using searchentries to find kinase or zinc finger domains. The SDK manages these calls asynchronously, allowing specialized agents to coordinate handoffs without blocking the main execution thread.

Q: Which EBI InterPro tool should my OpenAI Agents SDK agent call first to classify an unannotated sequence?

Your agent starts by calling searchproteins with the sequence name or keyword to find close matches. From there, it passes those accessions to getproteinentries to map the exact domain architecture.

Run production-ready bioinformatic agents that map protein domains using the OpenAI Agents SDK.

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Connect EBI InterPro MCP to OpenAI Agents SDK

Create your Vinkius account to connect EBI InterPro 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 EBI InterPro with OpenAI Agents SDK

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Map protein structures inside OpenAI Agents SDK workflows

The `get_entry_structures` tool pulls physical PDB coordinates for any annotated InterPro family directly into your OpenAI Agents SDK workflow. Your OpenAI Agents SDK pipeline calls this tool to retrieve precise structural representatives, resolving 3D functional constraints during multi-agent handoffs. If your OpenAI Agents SDK agent needs specific spatial details, it triggers `get_structure` with a 4-character PDB identifier. This prevents silent execution failures because the OpenAI dashboard traces every structural query from the EBI InterPro server and validates the payload before the next agent takes over.

Automate taxonomic profiling using this MCP Server

The `get_entry_taxonomy` tool exposes the taxonomic distribution of specific protein domains across the tree of life directly to your OpenAI Agents SDK. This SDK handles the discovery of this taxonomy tool automatically, passing raw phylogenetic ranks directly into your specialized classification agents. You map evolutionary conservation by running `get_taxonomy` inside your OpenAI Agents SDK setup to retrieve lineage details for specific host organisms. The SDK caches the EBI InterPro tool list using `cacheToolsList=True` to keep these deep taxonomic lookups fast and cheap during high-throughput biological screening.

Resolve multi-domain architecture with guardrailed search

The `get_protein_entries` tool identifies all functional domains living on a single amino acid chain for your OpenAI Agents SDK pipeline. This pipeline uses this tool to break down complex, multi-domain sequences before deciding which downstream agent should handle the annotation. When searching broad databases, the OpenAI Agents SDK agent initiates `search_proteins` to filter matches by organism and length. Built-in SDK guardrails validate these search parameters at the boundary, ensuring your agent never executes out-of-bounds queries on the EBI database via this MCP Server.

Setup guide

Set up EBI InterPro 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 EBI InterPro tools at runtime.
3

Create your Agent

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

Run the agent

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

You register the server by passing an `MCPServerStreamableHttp` instance directly into your agent configuration. Run `pip install openai-agents` first, point the server URL to your Vinkius endpoint, and set `mcp_servers=[server]` in your agent initialization.

Yes, your agents run concurrent lookups using `search_entries` to find kinase or zinc finger domains. The SDK manages these calls asynchronously, allowing specialized agents to coordinate handoffs without blocking the main execution thread.

The SDK relies on your Vinkius MCP connection to handle underlying HTTP transport details safely. You set `cacheToolsList=True` in your Python code to prevent redundant schema discoveries, which keeps your API footprint small and fast.

Your agent starts by calling `search_proteins` with the sequence name or keyword to find close matches. From there, it passes those accessions to `get_protein_entries` to map the exact domain architecture.

Your raw protein sequences and accession numbers never sit on persistent disks. The Vinkius sandbox executes every request inside an ephemeral V8 isolate, meaning your queries vanish from memory the instant the EBI API returns the domain classification.

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