AI NetCafé

Render a diagram from text

render_diagram

Read-onlyIdempotent

Turn diagram-as-code into an image: Mermaid, PlantUML, Graphviz/DOT, C4, Excalidraw and 20+ more (self-hosted Kroki). Returns a hosted SVG/PNG URL you can embed directly in Markdown or HTML. Example — GET "https://ainetcafe.com/t/render_diagram?source=graph TD;A--%3EB&format=png"

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "source": "<source>"
    },
    "name": "render_diagram"
  }
}

Input Schema

Name	Required	Description
`type`	No	Diagram language: mermaid (default), plantuml, graphviz, c4plantuml, excalidraw, blockdiag, erd…
`format`	No	"svg" (default) or "png".
`source`	Yes	The diagram source code (e.g. a Mermaid flowchart).

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedAug 4, 2026

TDQS

A4.5/5.0

Behavior4/5

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

With annotations already declaring readOnlyHint=true and idempotentHint=true, the description adds useful context by stating the result is a hosted SVG/PNG URL and mentions 'self-hosted Kroki', indicating the underlying service. The example also illustrates the endpoint usage. It does not cover auth or rate limits, but the annotations reduce the burden.

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 an example, with the core purpose stated first. The example includes a realistic URL but is not overly verbose. Every clause adds information: supported formats, output type, and usage pattern.

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

Completeness5/5

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

The tool is simple, and the description covers the essential aspects: what it does, supported formats, output format, and an example. The schema provides full parameter details, annotations cover safety, and an output schema exists. The description is sufficient for an agent to select and invoke the tool correctly.

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?

The schema already has 100% description coverage for all three parameters, so the baseline is 3. The description adds value by providing a concrete example of the query-string format (source=...&format=png) and clarifying the supported diagram types. This helps an agent understand parameter syntax beyond the schema.

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 opens with 'Turn diagram-as-code into an image' which clearly identifies both the action (rendering) and the object (diagram source text). It explicitly names supported languages (Mermaid, PlantUML, Graphviz/DOT, etc.), distinguishing it from sibling image-generation tools like text_to_image or make_chart. The purpose is unambiguous and specific.

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

Usage Guidelines4/5

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

The description clearly implies the tool is for diagram-as-code languages, giving context for when to use it. However, it does not explicitly contrast with alternatives or state when not to use it. An agent can infer use cases from the listed formats, but there are no direct exclusions or alternative recommendations.

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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