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generate_plot_securely

Generate line or scatter charts from numerical data in an isolated Azure sandbox, then save the plot as a PNG locally. Provides secure remote visualization for AI agents.

Instructions

Generate line or scatter charts from x and y data in an isolated Azure sandbox, enabling secure remote data visualization for AI agents.

ARCHITECTURE NOTE: The remote sandbox generates the plot, but the local MCP client intercepts the base64 payload and securely writes it directly to the user's local home directory as a PNG.

Use this tool to visually represent numerical trends. Keep data arrays under 10,000 points to prevent sandbox timeouts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xYesA list of numerical values for the X-axis. Must be the exact same length as y.
yYesA list of numerical values for the Y-axis. Must be the exact same length as x.
titleNoThe text string to display at the top of the chart.Data Plot
x_labelNoThe text string to label the X-axis.X
y_labelNoThe text string to label the Y-axis.Y
chart_typeNoThe visual style of the chart. Must be exactly 'line' or 'scatter'.line

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed6 schema fields changedv1.1.4
    • addedInput schema / properties / chart_type / description
      Added value: +"The visual style of the chart. Must be exactly 'line' or 'scatter'."
    • addedInput schema / properties / title / description
      Added value: +"The text string to display at the top of the chart."
    • addedInput schema / properties / x / description
      Added value: +"A list of numerical values for the X-axis. Must be the exact same length as y."
    • addedInput schema / properties / x_label / description
      Added value: +"The text string to label the X-axis."
    • addedInput schema / properties / y / description
      Added value: +"A list of numerical values for the Y-axis. Must be the exact same length as x."
    • addedInput schema / properties / y_label / description
      Added value: +"The text string to label the Y-axis."
  2. First observedv1.1.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the isolated Azure sandbox, the local interception of the base64 payload, and the secure writing of the PNG to the user's home directory. This is considerable transparency, though it does not detail file naming or overwrite behavior.

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 efficient and well-structured, leading with the core purpose and adding an architecture note. It is slightly longer than necessary but each sentence adds meaningful value, and the guidance is front-loaded.

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 moderate complexity, the description covers purpose, usage, security architecture, output location, and size constraints. An output schema exists, so return values are not needed. Minor gaps like file naming do not detract significantly from overall completeness.

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 schema already documents each parameter. The description adds the array size limit (under 10,000 points) and clarifies the x/y data relationship, but does not significantly enhance parameter semantics 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 clearly states the tool 'Generate line or scatter charts from x and y data', specifying both the action and resource. It effectively distinguishes this tool from siblings like execute_code_securely and sanitize_csv_securely by focusing on plot generation.

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 says 'Use this tool to visually represent numerical trends', providing contextual guidance for when to use it. It also includes a practical constraint about keeping data arrays under 10,000 points to avoid timeouts, but does not explicitly mention alternatives or when not to use it.

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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