.claude/skills/lab_protocol_from_literature/SKILL.md
Lab Protocol from Literature - Extract and generate lab protocol: search PubMed, extract protocol from paper, and generate executable protocol. Use this skill for lab science tasks involving pubmed search extract protocol from pdf protocol generation generate executable json. Combines 4 tools from 2 SCP server(s).
npx skillsauth add SpectrAI-Initiative/InnoClaw lab_protocol_from_literatureInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Lab Science | Tools Used: 4 | Servers: 2
Extract and generate lab protocol: search PubMed, extract protocol from paper, and generate executable protocol.
pubmed_search from search-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Searchextract_protocol_from_pdf from server-19 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Planprotocol_generation from server-19 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Plangenerate_executable_json from server-19 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Plan{
"query": "PCR amplification protocol for BRCA1"
}
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
from contextlib import AsyncExitStack
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client
SERVERS = {
"search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search",
"server-19": "https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Plan"
}
async def connect(url, stack):
transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
read, write, _ = await stack.enter_async_context(transport)
ctx = ClientSession(read, write)
session = await stack.enter_async_context(ctx)
await session.initialize()
return session
def parse(result):
try:
if hasattr(result, 'content') and result.content:
c = result.content[0]
if hasattr(c, 'text'):
try: return json.loads(c.text)
except: return c.text
return str(result)
except: return str(result)
async def main():
async with AsyncExitStack() as stack:
# Connect to required servers
sessions = {}
sessions["search-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search", stack)
sessions["server-19"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Plan", stack)
# Execute workflow steps
# Step 1: Search PubMed for protocols
result_1 = await sessions["search-server"].call_tool("pubmed_search", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Extract protocol from paper
result_2 = await sessions["server-19"].call_tool("extract_protocol_from_pdf", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Generate standard protocol
result_3 = await sessions["server-19"].call_tool("protocol_generation", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Create executable JSON
result_4 = await sessions["server-19"].call_tool("generate_executable_json", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
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