Skip to main content
Glama
pzfreo

build123d-mcp

render_drawing

Rasterizes SVG files to PNG images for inline viewing, enabling visualization of drawings created outside the sandbox without opening files separately.

Instructions

Rasterise an existing SVG file to PNG via resvg-py.

Complements render_view (which takes build123d shapes from the live
session) by accepting an SVG written outside the sandbox — typically by
a short Python script that does the ExportSVG call directly. The PNG is
returned inline so the LLM can see the drawing without you having to
open the file in another tool.

Args:
    svg_path: path to an SVG file on disk.
    width: output pixel width (default 1200); height set by SVG aspect ratio.
    save_to: optional path to write the PNG. If empty, PNG bytes are
        delivered inline only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
svg_pathYes
widthNo
save_toNo
Behavior3/5

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

No annotations provided, but description discloses core behavior: rasterization, inline return, optional save. Lacks details on error handling or overwriting behavior for save_to.

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?

Concise, well-structured: one-sentence purpose, context paragraph, then Args section. Every sentence adds value.

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

Completeness4/5

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

Covers input, output (inline PNG), and context. Lacks return format details but adequate given no output schema and no annotations.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining svg_path, width (default 1200, height by aspect ratio), and save_to (optional).

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?

Clearly states it rasterizes an SVG file to PNG via resvg-py. Distinguishes from sibling render_view which handles build123d shapes from the live session.

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

Usage Guidelines5/5

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

Explicitly says when to use (accepting SVG written outside sandbox) and contrasts with render_view. Mentions PNG returned inline so LLM can see drawing without opening file.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pzfreo/build123d-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server