Viz MCP Server

create_histogram

Generate histograms from numeric data with customizable bins, titles, labels, color palettes, and cumulative distribution options, outputting as SVG or PNG.

Instructions

Create a histogram.

Args: values: Numeric data points bins: Number of bins (default: 10) title: Chart title xlabel: X-axis label ylabel: Y-axis label palette: Color palette: default, vibrant, pastel, monochrome cumulative: Show cumulative distribution 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_histogram"
  }
}

Input Schema

Name	Required	Default
`values`	Yes
`bins`	No
`title`	No	Histogram
`xlabel`	No
`ylabel`	No	Frequency
`palette`	No	default
`cumulative`	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

A3.7/5.0

Behavior3/5

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

No annotations provided, so description bears full burden. It explains output options (svg vs png) and cumulative distribution, but does not mention side effects, permissions, or handling of edge cases like missing values.

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?

Description is concise with a clear opening statement followed by parameter list. Slightly lacking in structure (e.g., no bullet points), but no unnecessary content.

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 8 parameters and presence of output schema, description covers parameter semantics and output format choices. Could be enhanced with error handling or value constraints, but largely sufficient for a plotting tool.

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?

Schema description coverage is 0%, but description adds meaningful explanations for each parameter (e.g., 'Numeric data points', 'Number of bins (default: 10)'), compensating well beyond schema titles and types.

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?

Description clearly states 'Create a histogram,' a specific verb and resource. It distinguishes from sibling tools which are other chart types (bar, line, pie, scatter).

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 histogram versus alternative chart types. The description only lists parameters, not usage context or prerequisites.

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

Deploy Server