Skip to main content
Glama

create_canvas

Creates a canvas diagram from a structured description of nodes and connections. Returns the rendered PNG and the YAML recipe.

Instructions

Create a canvas diagram from a structured description. Provide a title, nodes, and connections — the tool handles layout and rendering. Returns the path to the rendered PNG and the generated YAML recipe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodesYesList of nodes to place on the canvas.
scaleNoRender scale factor (default 2.0)
titleYesTitle for the canvas diagram.
machinesNoOptional: group nodes into machines. Each item is a list of node IDs.
organizeNoApply the organize algorithm for automatic layout. Default: true.
orientationNoLayout direction: 'horizontal' (left→right, default) or 'vertical' (top→bottom tree).horizontal
spacing_levelNoSpacing level for organize layout. Default: 'container'.container
Behavior3/5

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

With no annotations, the description discloses that the tool handles layout and rendering and returns PNG path and YAML recipe. However, it omits behavioral traits such as idempotency, authentication needs, error handling, or side effects, which are important for safe invocation.

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: the first states the primary action, the second specifies required inputs and outputs. It is front-loaded and contains no superfluous words, earning its place efficiently.

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 7 parameters and no output schema, the description covers the main inputs and return values. It lacks details on constraints (e.g., node count limits) and explicit comparison to siblings, but is sufficient for a straightforward creation tool.

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 description coverage is 100%, so the baseline is 3. The description adds little beyond summarizing parameters ('title, nodes, and connections'). It does not enhance understanding of parameter formats or constraints beyond what the schema already provides.

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 creates a canvas diagram from a structured description, specifying the verb 'create' and resource 'canvas diagram'. It distinguishes from siblings like 'get_template' and 'list_templates', which deal with templates, and 'render_canvas', which likely renders an existing canvas.

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 tells users to provide title, nodes, and connections, implying inputs, but does not explicitly state when to use this tool versus alternatives like 'render_canvas'. No when-not or alternative guidance is provided, leaving usage context implied rather than explicit.

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/jdlongmire/ThinxAI-Canvas-MCP'

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