Biomedical Web Search

SkillSearch

Search biomedical literature and web content using Tavily search engine for research and clinical information.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Biomedical Web Search skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/scp in skills/biomedical-web-search/SKILL.md and read by ahel’s review.

Usage

import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

class OrigeneClient:
    def __init__(self, server_url: str, api_key: str):
        self.server_url = server_url
        self.api_key = api_key
        self.session = None

    async def connect(self):
        try:
            self.transport = streamablehttp_client(url=self.server_url, headers={"SCP-HUB-API-KEY": self.api_key})
            self.read, self.write, self.get_session_id = await self.transport.__aenter__()
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self.session_ctx.__aenter__()
            await self.session.initialize()
            return True
        except Exception as e:
            return False

    async def disconnect(self):
        if self.session:
            await self.session_ctx.__aexit__(None, None, None)
        if hasattr(self, 'transport'):
            await self.transport.__aexit__(None, None, None)

    def parse_result(self, result):
        if isinstance(result, dict):
            content_list = result.get("content") or []
        else:
            content_list = getattr(result, "content", []) or []
        texts = []
        for item in content_list:
            if isinstance(item, dict):
                if item.get("type") == "text":
                    texts.append(item.get("text") or "")
            else:
                if getattr(item, "type", None) == "text":
                    texts.append(getattr(item, "text", "") or "")
        return "".join(texts)

## Initialize and use
client = OrigeneClient("https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search", "<your-api-key>")
await client.connect()

result = await client.session.call_tool("tavily_search", arguments={"query": "brain tumor"})
print(client.parse_result(result))

await client.disconnect()

Tool: tavily_search

  • Args: query (str) - Search query
  • Returns: JSON with query, answer, results (URL, title, content, score)

Use Cases

  • Medical literature search, clinical research, disease information retrieval

Signals

GitHub stars
167
Forks
9
Last commit
Jun 2026
Advanced
Catalog kind
skill
Gateway key
biomedical-web-search
Source
github.com/internscience/scp