Viz MCP Server

create_pie_chart

Generate pie or donut charts from numeric values with customizable labels, colors, and percentage annotations. Supports SVG and PNG output.

Instructions

Create a pie / donut chart.

Args: values: Numeric values (proportions) labels: Slice labels (optional) title: Chart title palette: Color palette: default, vibrant, pastel, monochrome show_percent: Show percentage labels on slices output: 'svg' for inline SVG, 'png' for file path

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": {
      "values": "<values>"
    },
    "name": "create_pie_chart"
  }
}

Input Schema

Name	Required	Default
`values`	Yes
`labels`	No
`title`	No	Pie Chart
`palette`	No	default
`show_percent`	No
`output`	No	svg

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 18, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It lacks details on side effects (e.g., file creation for PNG output), data validation (e.g., values must be positive? sum to 100?), and error handling.

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

Conciseness4/5

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

The description is structured as a clear list with the purpose first. Some redundancy exists (e.g., 'Show percentage labels on slices' is obvious from parameter name 'show_percent'), but overall efficient.

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

Completeness3/5

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

Covers parameter details and output options. However, lacks usage guidance, behavioral traits, and constraints (e.g., label-value alignment). Incomplete for a tool with 6 parameters and no annotations.

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?

With 0% schema description coverage, the description compensates well by explaining each parameter: 'values: Numeric values (proportions)', 'labels: Slice labels (optional)', and enumerating palette options. Adds meaning beyond the schema's type and title.

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 starts with a clear verb and resource: 'Create a pie / donut chart.' This is specific and distinguishes it from sibling chart tools like create_bar_chart or create_line_chart.

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?

No guidance on when to use a pie chart versus alternatives (e.g., bar chart for comparisons). Missing context about suitability for proportional data vs. other chart types.

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

Deploy Server