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get_viewport_screenshot

Capture screenshots of the Blender 3D viewport to document your scene, share progress, or create reference images for AI-assisted modeling workflows.

Instructions

Capture a screenshot of the current Blender 3D viewport.

Parameters:
- max_size: Maximum size in pixels for the largest dimension (default: 800)

Returns the screenshot as an Image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_sizeNo

Implementation Reference

  • The main handler function for the 'get_viewport_screenshot' tool. It connects to Blender, sends a command to capture the viewport screenshot to a temporary file, reads the image bytes, and returns an MCP Image object.
    @mcp.tool()
    def get_viewport_screenshot(ctx: Context, max_size: int = 800) -> Image:
        """
        Capture a screenshot of the current Blender 3D viewport.
        
        Parameters:
        - max_size: Maximum size in pixels for the largest dimension (default: 800)
        
        Returns the screenshot as an Image.
        """
        try:
            blender = get_blender_connection()
            
            # Create temp file path
            temp_dir = tempfile.gettempdir()
            temp_path = os.path.join(temp_dir, f"blender_screenshot_{os.getpid()}.png")
            
            result = blender.send_command("get_viewport_screenshot", {
                "max_size": max_size,
                "filepath": temp_path,
                "format": "png"
            })
            
            if "error" in result:
                raise Exception(result["error"])
            
            if not os.path.exists(temp_path):
                raise Exception("Screenshot file was not created")
            
            # Read the file
            with open(temp_path, 'rb') as f:
                image_bytes = f.read()
            
            # Delete the temp file
            os.remove(temp_path)
            
            return Image(data=image_bytes, format="png")
            
        except Exception as e:
            logger.error(f"Error capturing screenshot: {str(e)}")
            raise Exception(f"Screenshot failed: {str(e)}")
  • The @mcp.tool() decorator registers the get_viewport_screenshot function as an MCP tool.
    @mcp.tool()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the action and return type ('Returns the screenshot as an Image'). It misses critical behavioral details: whether it captures the active viewport only, if it requires specific Blender modes, potential performance impacts, or error conditions (e.g., no viewport open).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by a concise parameter explanation and return statement. Every sentence adds value without waste, and the structure is logical and efficient for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (interacting with Blender's viewport) and lack of annotations or output schema, the description is incomplete. It omits details like image format, handling of multiple viewports, or error responses, which are essential for an AI agent to use it correctly in varied scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining the single parameter's purpose ('Maximum size in pixels for the largest dimension') and default value, adding meaningful context beyond the schema's basic type and title. Since there's only one parameter, this is sufficient for clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Capture a screenshot') and target resource ('current Blender 3D viewport'), distinguishing it from sibling tools that handle downloads, code execution, model generation, or scene queries. It precisely defines what the tool does without redundancy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as whether it's for debugging, documentation, or preview purposes. It lacks context about prerequisites (e.g., Blender must be running) or exclusions, leaving usage unclear beyond the basic action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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