ucsc_genome_exploration

# UCSC Genome Browser Exploration

**Discipline**: Genomics | **Tools Used**: 5 | **Servers**: 1

## Description

Explore genome via UCSC: list genomes, list tracks, get sequence, get track data, and cytoband info.

## Tools Used

- **`list_genomes`** from `ucsc-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC`
- **`list_tracks`** from `ucsc-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC`
- **`get_sequence`** from `ucsc-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC`
- **`get_track_data`** from `ucsc-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC`
- **`get_cytoband`** from `ucsc-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC`

## Workflow

1. List available genomes
2. List tracks for hg38
3. Get DNA sequence for BRCA1 region
4. Get track data
5. Get cytoband info

## Test Case

### Input
```json
{
    "genome": "hg38",
    "chrom": "chr17",
    "start": 43044295,
    "end": 43125370
}
```

### Expected Steps
1. List available genomes
2. List tracks for hg38
3. Get DNA sequence for BRCA1 region
4. Get track data
5. Get cytoband info

## 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 = {
    "ucsc-server": "https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC"
}

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["ucsc-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC", stack)

        # Execute workflow steps
        # Step 1: List available genomes
        result_1 = await sessions["ucsc-server"].call_tool("list_genomes", arguments={})
        data_1 = parse(result_1)
        print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

        # Step 2: List tracks for hg38
        result_2 = await sessions["ucsc-server"].call_tool("list_tracks", arguments={})
        data_2 = parse(result_2)
        print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

        # Step 3: Get DNA sequence for BRCA1 region
        result_3 = await sessions["ucsc-server"].call_tool("get_sequence", arguments={})
        data_3 = parse(result_3)
        print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

        # Step 4: Get track data
        result_4 = await sessions["ucsc-server"].call_tool("get_track_data", arguments={})
        data_4 = parse(result_4)
        print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

        # Step 5: Get cytoband info
        result_5 = await sessions["ucsc-server"].call_tool("get_cytoband", arguments={})
        data_5 = parse(result_5)
        print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")

        # Cleanup
        print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```