Skip to main content
Glama

Generate SVG Graphic

generate_svg

Turn prompts into production-ready SVG code for diagrams, illustrations, icons, and charts. Preview the result inline and save the graphic.

Instructions

Generate scalable vector graphics (SVG) using Gemini. Creates clean, production-ready SVG code for diagrams, illustrations, icons, and data visualizations. Returns inline preview with SVG viewer. [MCP_RECOMMENDED_TIMEOUT_MS: 240000]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOmit to use gemini-3.1-pro-preview. Other valid options: gemini-3-pro-preview, gemini-3-flash-preview.
styleNoVisual style: technical (diagrams), artistic (illustrations), minimal (simple), data-viz (charts)technical
widthNoSVG width in pixels (default: 800)
heightNoSVG height in pixels (default: 600)
promptYesDescription of the SVG graphic to generate
outputPathNoOptional file path to save the SVG (e.g. C:/output/diagram.svg)
Behavior3/5

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

Without annotations, the description carries the transparency burden. It mentions the inline preview and a recommended timeout, which gives operational insight. However, it does not disclose side effects like file writing when outputPath is provided, whether the operation is read-only, or any permission requirements. The generative nature implies creation, but this is not explicitly stated.

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 two sentences plus a timeout note, with the primary action stated upfront. Every sentence adds value: the first defines purpose, the second describes output and preview, and the timeout note is practical. No filler or redundancy.

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?

Given the tool's complexity (6 parameters, no annotations, no output schema), the description is fairly complete. It covers what it generates, the output format, and a timeout recommendation. However, it omits details like error handling, whether outputPath is required for saving, and how to specify style constraints beyond schema enums. These gaps are minor for a generation tool but prevent a higher score.

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

Parameters3/5

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

Schema coverage is 100%, so parameter descriptions already exist. The tool description adds contextual value by naming the types of graphics (diagrams, icons, etc.) but does not elaborate on parameter usage beyond what the schema provides. It meets the baseline for full schema coverage without adding significant new meaning.

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 tool generates SVG graphics via Gemini, listing specific use cases (diagrams, illustrations, icons, data visualizations). This distinguishes it from sibling tools like generate_image (which likely produces raster images) and edit_image (which modifies existing images), making the purpose specific and unambiguous.

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

Usage Guidelines3/5

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

The description implies usage for vector graphic creation but does not explicitly state when to prefer this over alternatives such as generate_image or when not to use it. It provides context (SVG, data visualization) but lacks direct guidance on tool selection or exclusion criteria.

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/houtini-ai/gemini-mcp'

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