mobility-analysis

# Charge Carrier Mobility Analysis **Discipline**: Semiconductor Physics | **Tools Used**: 4 | **Servers**: 2 ## Description Analyze carrier mobility: calculate new mobility, compute vacuum permittivity, and error analysis. ## Tools Used - **`calculate_new_mobility`** from `server-21` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations` - **`calculate_vacuum_permittivity`** from `server-21` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations` - **`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` ## Workflow 1. Calculate new mobility 2. Compute vacuum permittivity 3. Calculate measurement error 4. Compute mean square statistics ## Test Case ### Input ```json { "mobility_data": [ 1500, 1450, 1520 ] } ``` ### Expected Steps 1. Calculate new mobility 2. Compute vacuum permittivity 3. Calculate measurement error 4. Compute mean square statistics ## Usage Example > **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn). ```python import asyncio import json from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client from mcp.client.sse import sse_client SERVERS = { "server-21": "https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations", "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, transport 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(): # Connect to required servers sessions = {} sessions["server-21"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations", "streamable-http") 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 new mobility result_1 = await sessions["server-21"].call_tool("calculate_new_mobility", arguments={}) data_1 = parse(result_1) print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}") # Step 2: Compute vacuum permittivity result_2 = await sessions["server-21"].call_tool("calculate_vacuum_permittivity", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Calculate measurement error result_3 = await sessions["server-26"].call_tool("calculate_absolute_error", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Compute mean square statistics result_4 = await sessions["server-26"].call_tool("calculate_mean_square", 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()) ```