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screen-mcp

screen-mcp

by ferre-z
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Screenshot & Analyze

screenshot_and_analyze
Read-only

Capture a specific screen region and get instant Gemini analysis in one call. Provide coordinates and a prompt to answer questions about on-screen content for agents without vision.

Instructions

Capture a screen region and immediately send it to Gemini for analysis in a single call. Combines screenshot_region and analyze_image. Useful for agents without native vision.

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": {
      "x": "<x>",
      "y": "<y>",
      "width": "<width>",
      "height": "<height>",
      "prompt": "<prompt>"
    },
    "name": "screenshot_and_analyze"
  }
}

Input Schema

NameRequiredDescriptionDefault
xYesTop-left X coordinate in pixels
yYesTop-left Y coordinate in pixels
modelNoGemini model to use (default: gemini-2.5-flash)
scaleNoDownscale factor for the screenshot before sending to Gemini
widthYesRegion width in pixels
heightYesRegion height in pixels
promptYesWhat to analyze or ask about the screenshot
include_cursorNoInclude the mouse cursor in the screenshot

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds context by revealing it is a composite operation ('Combines screenshot_region and analyze_image') and explains its utility for agents without native vision. It does not contradict annotations, and it adds useful behavioral context beyond the structured fields.

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, front-loaded with the primary action, and contains no fluff. Every sentence adds value: the first explains what it does, the second provides context and usage guidance. It is appropriately sized for the tool's complexity.

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 has 8 parameters, no output schema, and is a composite of two tools, the description is mostly complete. It explains the purpose, usage context, and composition. However, it does not explicitly state what the tool returns (the Gemini analysis), though this is implied by 'send it to Gemini for analysis.' Minor gap, but adequate for an agent to use it effectively.

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 all 8 parameters are already well-documented in the input schema. The description adds minimal parameter-specific meaning—it implicitly clarifies that x, y, width, height define the region and prompt is the analysis question, but this is already evident from the schema. It does not elaborate on scale or model, but the schema covers those. Baseline of 3 is appropriate.

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 action: 'Capture a screen region and immediately send it to Gemini for analysis in a single call.' It specifies the resource (screen region) and the purpose (analysis), and distinguishes itself by noting it combines screenshot_region and analyze_image, setting it apart from sibling tools.

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 provides a clear use case: 'Useful for agents without native vision.' This indicates when to prefer this tool over alternatives. However, it does not explicitly state when not to use it or mention alternative tools like calling screenshot_region and analyze_image separately, so it lacks exclusions.

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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