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duke0317

Image Processing MCP Server

by duke0317

apply_contour

Apply contour filters to images to detect and highlight edges and boundaries for enhanced visual analysis.

Instructions

应用轮廓滤镜

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_sourceYes图片源,可以是文件路径或base64编码的图片数据

Implementation Reference

  • Core handler function that loads the image, applies PIL's ImageFilter.CONTOUR filter, processes output via ImageProcessor, and returns JSON result with processed image data.
    async def apply_contour(image_data: str) -> list[TextContent]:
        """
        应用轮廓滤镜
        
        Args:
            image_data: 图片数据(base64编码)
            
        Returns:
            应用滤镜后的图片数据
        """
        try:
            # 验证参数
            if not image_data:
                raise ValidationError("图片数据不能为空")
            
            # 加载图片
            image = processor.load_image(image_data)
            
            # 应用轮廓滤镜
            contour_image = image.filter(ImageFilter.CONTOUR)
            
            # 输出处理后的图片
            output_info = processor.output_image(contour_image, "contour")
            
            result = {
                "success": True,
                "message": "轮廓滤镜应用成功",
                "data": {
                    **output_info,
                    "filter_type": "contour",
                    "size": image.size
                }
            }
            
            return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))]
            
        except ValidationError as e:
            error_result = {
                "success": False,
                "error": f"参数验证失败: {str(e)}"
            }
            return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))]
            
        except Exception as e:
            error_result = {
                "success": False,
                "error": f"轮廓滤镜应用失败: {str(e)}"
            }
            return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))]
  • main.py:340-352 (registration)
    MCP server tool registration using @mcp.tool() decorator. Wraps the filters.apply_contour handler with safe_run_async and error handling.
    @mcp.tool()
    def apply_contour(
        image_source: Annotated[str, Field(description="图片源,可以是文件路径或base64编码的图片数据")]
    ) -> str:
        """应用轮廓滤镜"""
        try:
            result = safe_run_async(filters_apply_contour(image_source))
            return result[0].text
        except Exception as e:
            return json.dumps({
                "success": False,
                "error": f"应用轮廓效果失败: {str(e)}"
            }, ensure_ascii=False, indent=2)
  • Input schema definition for the apply_contour tool in the get_filter_tools() function (possibly auxiliary or legacy).
    Tool(
        name="apply_contour",
        description="应用轮廓滤镜",
        inputSchema={
            "type": "object",
            "properties": {
                "image_data": {
                    "type": "string",
                    "description": "图片数据(base64编码)"
                }
            },
            "required": ["image_data"]
        }
    ),

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