uniprot_deep_analysis: Скилл глубокого анализа белков

--- name: uniprot_deep_analysis description: "UniProt Deep Protein Analysis - Deep UniProt analysis: entry data, UniRef clusters, UniParc cross-references, and gene-centric view. Use this skill for protein science tasks involving get uniprotkb entry by accession get uniref cluster by id get uniparc entry by upi get gene centric by accession. Combines 4 tools from 1 SCP server(s)." --- # UniProt Deep Protein Analysis **Discipline**: Protein Science | **Tools Used**: 4 | **Servers**: 1 ## Description Deep UniProt analysis: entry data, UniRef clusters, UniParc cross-references, and gene-centric view. ## Tools Used - **`get_uniprotkb_entry_by_accession`** from `uniprot-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt` - **`get_uniref_cluster_by_id`** from `uniprot-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt` - **`get_uniparc_entry_by_upi`** from `uniprot-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt` - **`get_gene_centric_by_accession`** from `uniprot-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt` ## Workflow 1. Get UniProtKB entry 2. Get UniRef cluster 3. Get UniParc entry 4. Get gene-centric data ## Test Case ### Input ```json { "accession": "P04637", "uniref_id": "UniRef90_P04637", "uniparc_id": "UPI0000000001" } ``` ### Expected Steps 1. Get UniProtKB entry 2. Get UniRef cluster 3. Get UniParc entry 4. Get gene-centric data ## Usage Example > **Note:** Replace `sk-b04409a1-b32b-4511-9aeb-22980abdc05c` 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 contextlib import AsyncExitStack from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client from mcp.client.sse import sse_client SERVERS = { "uniprot-server": "https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt" } 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["uniprot-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt", stack) # Execute workflow steps # Step 1: Get UniProtKB entry result_1 = await sessions["uniprot-server"].call_tool("get_uniprotkb_entry_by_accession", arguments={}) data_1 = parse(result_1) print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}") # Step 2: Get UniRef cluster result_2 = await sessions["uniprot-server"].call_tool("get_uniref_cluster_by_id", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Get UniParc entry result_3 = await sessions["uniprot-server"].call_tool("get_uniparc_entry_by_upi", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Get gene-centric data result_4 = await sessions["uniprot-server"].call_tool("get_gene_centric_by_accession", 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()) ```