88 lines
3.5 KiB
Python
88 lines
3.5 KiB
Python
from mcp.server.fastmcp.server import FastMCP
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from pydantic import BaseModel, ValidationError
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import jsonschema
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import uvicorn
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import logging
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from jsonschema import validate, ValidationError
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from mcp.server.fastmcp.server import FastMCP
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# 新增导入
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from response_utils import extract_data_for_validation
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mcp = FastMCP(
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"SchemaValidatorServer",
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title="JSON Schema Validator Server",
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description="A server that provides a tool to validate data against a JSON Schema.",
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version="0.1.0"
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)
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@mcp.tool()
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def validate_schema(data_instance: dict, schema: dict) -> dict:
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"""
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Validates a data instance against a given JSON Schema.
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Args:
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data_instance: The data object to validate.
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schema: The JSON Schema to validate against.
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Returns:
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A dictionary containing the validation result.
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{"isValid": True} on success.
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{"isValid": False, "error": "Validation error message"} on failure.
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"""
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try:
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jsonschema.validate(instance=data_instance, schema=schema)
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return {"isValid": True, "error": None}
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except ValidationError as e:
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logging.error(f"SchemaValidator: Validation failed. Error: {e.message}", exc_info=True)
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return {"isValid": False, "error": e.message}
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except Exception as e:
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# Catch other potential errors from the jsonschema library
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return {"isValid": False, "error": str(e)}
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@mcp.tool()
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def validate_flexible_schema(api_response: dict, item_schema: dict) -> dict:
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"""
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对一个可能带有标准包装（如 {code, message, data}）的API响应进行灵活的schema验证。
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它能自动提取核心业务数据（无论是单个对象还是列表）并逐项进行验证。
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Args:
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api_response (dict): 完整的API响应体。
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item_schema (dict): 描述核心业务数据**单个元素**的JSON Schema。
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Returns:
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dict: 一个包含验证结果的字典, {"isValid": True} 或 {"isValid": False, "error": "..."}。
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"""
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logging.info("SchemaValidator: Running flexible validation...")
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try:
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# 使用工具函数提取需要验证的数据
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items_to_validate = extract_data_for_validation(api_response)
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if not items_to_validate:
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error_message = "Flexible validation failed: Could not extract any items to validate from the response."
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logging.warning(error_message)
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return {"isValid": False, "error": error_message}
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logging.info(f"Flexible validation: Extracted {len(items_to_validate)} item(s) to validate.")
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# 逐个验证提取出的项
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for i, item in enumerate(items_to_validate):
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validate(instance=item, schema=item_schema)
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logging.info(f" -> Item {i+1}/{len(items_to_validate)} passed validation.")
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logging.info("SchemaValidator: Flexible validation successful. All items conform to the schema.")
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return {"isValid": True}
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except ValidationError as e:
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error_message = f"Flexible validation failed on an item. Error: {e.message}"
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logging.error(error_message, exc_info=True)
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return {"isValid": False, "error": error_message}
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except Exception as e:
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error_message = f"An unexpected error occurred during flexible validation: {e}"
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logging.error(error_message, exc_info=True)
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return {"isValid": False, "error": error_message}
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# --- 启动服务器 ---
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if __name__ == "__main__":
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uvicorn.run(mcp.streamable_http_app(), host="127.0.0.1", port=8002) |