# API快速参考
## 🟢 可用API快速参考
### KEGG API
```bash
# 基础URL
https://rest.kegg.jp/
# 常用端点
GET /list/pathway # 通路列表
GET /link/pathway/hsa:TP53 # 基因-通路关联
GET /find/genes/cancer # 基因搜索
```
### STRING API
```bash
# 基础URL
https://string-db.org/api/
# 常用端点
GET /json/network?identifiers=TP53&species=9606
GET /json/functional_annotation?identifiers=TP53
GET /json/enrichment?identifiers=TP53&species=9606
```
### UniProt API
```bash
# 基础URL
https://rest.uniprot.org/uniprotkb/
# 常用端点
GET /P04637 # 蛋白质信息
GET /P04637.fasta # FASTA序列
GET /search?query=organism_id:9606 # 高级搜索
```
### Ensembl API
```bash
# 基础URL
https://rest.ensembl.org/
# 常用端点
GET /lookup/id/ENSG00000141510
GET /homology/id/ENSG00000141510?type=orthologues
GET /overlap/region/human/17:7565097-7590856?feature=gene
```
---
## 🛠️ 推荐的MCP工具实现模板
```python
@mcp.tool()
async def kegg_pathway_analysis(
gene_list: list[str],
organism: str = "hsa"
) -> dict[str, Any]:
"""KEGG通路分析工具"""
# 实现 KEGG API 调用
pass
@mcp.tool()
async def string_network_analysis(
proteins: list[str],
species: int = 9606,
confidence: float = 0.4
) -> dict[str, Any]:
"""STRING蛋白质互作网络分析"""
# 实现 STRING API 调用
pass
@mcp.tool()
async def ensembl_comparative_analysis(
gene_id: str,
target_species: list[str]
) -> dict[str, Any]:
"""Ensembl跨物种比较分析"""
# 实现 Ensembl API 调用
pass
```
---
## 📋 优先级建议
1. **立即实现**: KEGG, STRING, UniProt, Ensembl
2. **需要研究**: Reactome, QuickGO
3. **暂时避免**: BioGRID, RCSB PDB
---
*详细调研报告请参考：[bioinformatics_apis_research.md](./bioinformatics_apis_research.md)*