get_data
Retrieve genomic data by automatically identifying query types for genes, proteins, regions, or evolutionary analysis.
Instructions
智能数据获取接口 - 统一处理所有查询类型
自动识别查询类型：
"TP53" → 基因信息查询
"P04637" → 蛋白质详细信息查询
"cancer" → 基因搜索
"protein kinase" → 蛋白质功能搜索
"chr17:7565097-7590856" → 区域搜索
"TP53, BRCA1" → 批量基因信息
"breast cancer genes" → 智能搜索
"TP53 homologs" → 同源基因查询
"evolutionary conservation" → 进化分析查询
Args: query: 查询内容（可以是基因ID、蛋白质ID、搜索词、区域、ID列表、进化相关查询） query_type: 查询类型（auto/info/search/region/protein/gene_protein/ortholog/evolution） data_type: 数据类型（gene/protein/gene_protein/ortholog/evolution） format: 返回格式（simple/detailed/raw） species: 物种（默认：human，支持9606/human/mouse/rat等） max_results: 最大结果数（默认：20）
Returns: 查询结果字典，包含基因和/或蛋白质信息
Examples: # 基因信息查询 get_data("TP53") get_data("TP53", format="detailed")
# 批量查询
get_data(["TP53", "BRCA1", "BRCA2"])
# 区域搜索
get_data("chr17:7565097-7590856")
# 蛋白质查询
get_data("P04637", data_type="protein")
# 基因-蛋白质整合查询
get_data("TP53", data_type="gene_protein")
# 蛋白质功能搜索
get_data("tumor suppressor", data_type="protein")
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| query_type | No | auto | |
| data_type | No | gene | |
| format | No | simple | |
| species | No | human | |
| max_results | No |
Input Schema (JSON Schema)
{
"properties": {
"data_type": {
"default": "gene",
"type": "string"
},
"format": {
"default": "simple",
"type": "string"
},
"max_results": {
"default": 20,
"type": "integer"
},
"query": {
"anyOf": [
{
"type": "string"
},
{
"items": {
"type": "string"
},
"type": "array"
}
]
},
"query_type": {
"default": "auto",
"type": "string"
},
"species": {
"default": "human",
"type": "string"
}
},
"required": [
"query"
],
"type": "object"
}
Implementation Reference
- src/genome_mcp/core/tools.py:253-351 (handler)The primary handler implementation for the 'get_data' MCP tool. This async function handles input validation, query parsing using QueryParser, execution via QueryExecutor, result formatting, and error handling.@mcp.tool() async def get_data( query: str | list[str], query_type: str = "auto", data_type: str = "gene", format: str = "simple", species: str = "human", max_results: int = 20, ) -> ToolResult: """ 智能数据获取接口 - 统一处理所有查询类型 自动识别查询类型： - "TP53" → 基因信息查询 - "P04637" → 蛋白质详细信息查询 - "cancer" → 基因搜索 - "protein kinase" → 蛋白质功能搜索 - "chr17:7565097-7590856" → 区域搜索 - "TP53, BRCA1" → 批量基因信息 - "breast cancer genes" → 智能搜索 - "TP53 homologs" → 同源基因查询 - "evolutionary conservation" → 进化分析查询 Args: query: 查询内容（可以是基因ID、蛋白质ID、搜索词、区域、ID列表、进化相关查询） query_type: 查询类型（auto/info/search/region/protein/gene_protein/ortholog/evolution） data_type: 数据类型（gene/protein/gene_protein/ortholog/evolution） format: 返回格式（simple/detailed/raw） species: 物种（默认：human，支持9606/human/mouse/rat等） max_results: 最大结果数（默认：20） Returns: 查询结果字典，包含基因和/或蛋白质信息 Examples: # 基因信息查询 get_data("TP53") get_data("TP53", format="detailed") # 批量查询 get_data(["TP53", "BRCA1", "BRCA2"]) # 区域搜索 get_data("chr17:7565097-7590856") # 蛋白质查询 get_data("P04637", data_type="protein") # 基因-蛋白质整合查询 get_data("TP53", data_type="gene_protein") # 蛋白质功能搜索 get_data("tumor suppressor", data_type="protein") """ try: # 验证通用参数 validated_max_results, validated_species, validated_query_type = ( validate_common_params( max_results=max_results, species=species, query_type=query_type ) ) # 根据data_type参数调整查询类型 if data_type == "protein" and validated_query_type == "auto": validated_query_type = "protein" elif data_type == "gene_protein" and validated_query_type == "auto": validated_query_type = "gene_protein" elif data_type == "ortholog" and validated_query_type == "auto": validated_query_type = "ortholog" elif data_type == "evolution" and validated_query_type == "auto": validated_query_type = "evolution" elif data_type == "gene" and validated_query_type == "auto": validated_query_type = "auto" # 保持原有的自动识别 # 解析查询意图 parsed = QueryParser.parse(query, validated_query_type) # 使用验证后的物种信息 if "organism" not in parsed.params: parsed.params["organism"] = validated_species # 执行查询 result = await _query_executor.execute( parsed, max_results=validated_max_results ) # 格式化结果 if format == "simple": return _format_simple_result(result) elif format == "detailed": return result else: return result except ValidationError as e: return format_simple_error(e, query=query, operation="get_data") except Exception as e: return format_simple_error(e, query=query, operation="get_data")
- src/genome_mcp/main.py:34-41 (registration)Top-level registration where create_mcp_tools is imported and invoked on the FastMCP instance, registering the get_data tool among others.from .core.tools import create_mcp_resources, create_mcp_tools # 创建MCP实例 mcp = FastMCP("Genome MCP", version="0.2.5") # 注册所有资源和工具 create_mcp_resources(mcp) create_mcp_tools(mcp)
- src/genome_mcp/core/tools.py:250-252 (registration)The create_mcp_tools function defines and registers the get_data tool using the @mcp.tool() decorator.def create_mcp_tools(mcp: FastMCP) -> None: """创建并注册所有MCP工具"""