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version: "1.0.1" name: experimental_data_processing description: "Experimental Data Processing - Process experimental data: absolute error, mean square, max value, scientific notation formatting. Use this skill for experimental physics tasks involving calculate absolute error calculate mean square calculate max value format scientific notation convert to scientific notation. Combines 5 tools from 1 SCP server(s)."
Experimental Data Processing
Discipline: Experimental Physics | Tools Used: 5 | Servers: 1
Description
Process experimental data: absolute error, mean square, max value, scientific notation formatting.
Tools Used
- `calculate_absolute_error` from
server-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis - `calculate_mean_square` from
server-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis - `calculate_max_value` from
server-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis - `format_scientific_notation` from
server-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis - `convert_to_scientific_notation` from
server-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis
Workflow
- Calculate absolute errors
- Compute mean square
- Find maximum
- Format in scientific notation
- Summarize results
Test Case
Input
json
{"measurements": [9.78,9.81,9.83,9.79,9.8],"true_value": 9.81}
Expected Steps
- Calculate absolute errors
- Compute mean square
- Find maximum
- Format in scientific notation
- Summarize results
Usage Example
Note: Replace<YOUR_SCP_HUB_API_KEY>with your own SCP Hub API Key. You can obtain one from the SCP Platform.
python
import asyncioimport jsonfrom mcp import ClientSessionfrom mcp.client.streamable_http import streamablehttp_clientfrom mcp.client.sse import sse_clientSERVERS = {"server-26": "https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis"}async def connect(url, transport_type):transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})read, write, _ = await transport.__aenter__()ctx = ClientSession(read, write)session = await ctx.__aenter__()await session.initialize()return session, ctx, transportdef 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.textreturn str(result)except: return str(result)async def main():# Connect to required serverssessions = {}sessions["server-26"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis", "streamable-http")# Execute workflow steps# Step 1: Calculate absolute errorsresult_1 = await sessions["server-26"].call_tool("calculate_absolute_error", arguments={})data_1 = parse(result_1)print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")# Step 2: Compute mean squareresult_2 = await sessions["server-26"].call_tool("calculate_mean_square", arguments={})data_2 = parse(result_2)print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")# Step 3: Find maximumresult_3 = await sessions["server-26"].call_tool("calculate_max_value", arguments={})data_3 = parse(result_3)print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")# Step 4: Format in scientific notationresult_4 = await sessions["server-26"].call_tool("format_scientific_notation", arguments={})data_4 = parse(result_4)print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")# Step 5: Summarize resultsresult_5 = await sessions["server-26"].call_tool("convert_to_scientific_notation", arguments={})data_5 = parse(result_5)print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")# Cleanupprint("Workflow complete!")if __name__ == "__main__":asyncio.run(main())