Image Processing MCP Server

Instructions

Implementation Reference

• tools/transform.py:138-227 (handler)

  Core handler function that performs the image resizing using PIL, with aspect ratio handling, resampling, validation, and JSON output.

  async def resize_image(image_source: str, width: int, height: int, 
                        keep_aspect_ratio: bool = True, resample: str = "LANCZOS") -> list[TextContent]:
      """
      调整图片大小
      
      Args:
          image_source: 图片源（文件路径或base64编码数据）
          width: 目标宽度
          height: 目标高度
          keep_aspect_ratio: 是否保持宽高比
          resample: 重采样方法
          
      Returns:
          调整后的图片数据
      """
      try:
          # 验证参数
          if not image_source:
              raise ValidationError("图片源不能为空")
          
          ensure_valid_dimensions(width, height)
          
          # 验证重采样方法
          resample_methods = {
              'NEAREST': Image.NEAREST,
              'BILINEAR': Image.BILINEAR,
              'BICUBIC': Image.BICUBIC,
              'LANCZOS': Image.LANCZOS
          }
          
          if resample.upper() not in resample_methods:
              raise ValidationError(f"不支持的重采样方法: {resample}")
          
          # 加载图片
          image = processor.load_image(image_source)
          original_size = image.size
          
          # 计算目标尺寸
          if keep_aspect_ratio:
              # 保持宽高比，计算实际尺寸
              aspect_ratio = original_size[0] / original_size[1]
              target_aspect_ratio = width / height
              
              if aspect_ratio > target_aspect_ratio:
                  # 以宽度为准
                  new_width = width
                  new_height = int(width / aspect_ratio)
              else:
                  # 以高度为准
                  new_height = height
                  new_width = int(height * aspect_ratio)
          else:
              new_width, new_height = width, height
          
          # 调整大小
          resized_image = image.resize(
              (new_width, new_height), 
              resample_methods[resample.upper()]
          )
          
          # 输出调整后的图片
          output_info = processor.output_image(resized_image, f"resize_{new_width}x{new_height}")
          
          result = {
              "success": True,
              "message": f"图片大小调整成功: {original_size} -> {(new_width, new_height)}",
              "data": {
                  **output_info,
                  "original_size": original_size,
                  "new_size": (new_width, new_height),
                  "keep_aspect_ratio": keep_aspect_ratio,
                  "resample_method": resample
              }
          }
          
          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"图片大小调整失败: {str(e)}"
          }
          return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))]

• main.py:170-186 (registration)

  MCP tool registration using @mcp.tool() decorator, defines input schema via Annotated fields, and delegates to the core transform_resize_image implementation.

  @mcp.tool()
  def resize_image(
      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")],
      width: Annotated[int, Field(description="目标宽度（像素）", gt=0)],
      height: Annotated[int, Field(description="目标高度（像素）", gt=0)],
      keep_aspect_ratio: Annotated[bool, Field(description="是否保持宽高比，True时会按比例缩放", default=True)],
      resample: Annotated[str, Field(description="重采样算法：LANCZOS（高质量）、BILINEAR（平滑）、NEAREST（快速）", default="LANCZOS")]
  ) -> str:
      """调整图片大小"""
      try:
          result = safe_run_async(transform_resize_image(image_source, width, height, keep_aspect_ratio, resample))
          return result[0].text
      except Exception as e:
          return json.dumps({
              "success": False,
              "error": f"调整图片大小失败: {str(e)}"
          }, ensure_ascii=False, indent=2)

• tools/transform.py:12-47 (schema)

  Tool schema definition including input schema, properties, constraints, and defaults for resize_image.

  Tool(
      name="resize_image",
      description="调整图片大小",
      inputSchema={
          "type": "object",
          "properties": {
              "image_data": {
                  "type": "string",
                  "description": "图片数据（base64编码）"
              },
              "width": {
                  "type": "integer",
                  "description": "目标宽度",
                  "minimum": 1,
                  "maximum": 4096
              },
              "height": {
                  "type": "integer",
                  "description": "目标高度",
                  "minimum": 1,
                  "maximum": 4096
              },
              "keep_aspect_ratio": {
                  "type": "boolean",
                  "description": "是否保持宽高比",
                  "default": True
              },
              "resample": {
                  "type": "string",
                  "description": "重采样方法（NEAREST, BILINEAR, BICUBIC, LANCZOS）",
                  "default": "LANCZOS"
              }
          },
          "required": ["image_data", "width", "height"]
      }
  ),