ucsc_genome_exploration
UCSC Genome Browser Exploration - Explore genome via UCSC: list genomes, list tracks, get sequence, get track data, and cytoband info. Use this skill for genomics tasks involving list genomes list tracks get sequence get track data get cytoband. Combines 5 tools from 1 SCP server(s).
Best use case
ucsc_genome_exploration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
UCSC Genome Browser Exploration - Explore genome via UCSC: list genomes, list tracks, get sequence, get track data, and cytoband info. Use this skill for genomics tasks involving list genomes list tracks get sequence get track data get cytoband. Combines 5 tools from 1 SCP server(s).
Teams using ucsc_genome_exploration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ucsc_genome_exploration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ucsc_genome_exploration Compares
| Feature / Agent | ucsc_genome_exploration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
UCSC Genome Browser Exploration - Explore genome via UCSC: list genomes, list tracks, get sequence, get track data, and cytoband info. Use this skill for genomics tasks involving list genomes list tracks get sequence get track data get cytoband. Combines 5 tools from 1 SCP server(s).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 `<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 = {
"ucsc-server": "https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC"
}
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["ucsc-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/13/Origene-UCSC", "streamable-http")
# 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())
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