Skip to main content
Glama
Sign In
Screen Control

Screen Control

by Xeakaes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

screenshot

Capture the screen as an image to give vision-capable AI models visual context. Use region, scale, and quality parameters to tailor the capture.

Instructions

Capture the screen as an image (for vision-capable models). 'region' = "x,y,w,h"; 'scale' 0-1 shrinks to save bandwidth; 'quality' 1-100.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "screenshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
scaleNo
regionNo
monitorNo
qualityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are present, so the description carries the full burden. It does explain parameter behavior (scale shrinks to save bandwidth, quality range, region format), which is useful. However, it does not explicitly state that the operation is read-only, nor does it disclose output format, permission requirements, or multi-monitor behavior.

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?

Two sentences with zero filler. The main purpose is front-loaded, and the parameter hints are compact and actionable. Nothing extraneous is included.

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

Completeness2/5

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

Given no output schema, no annotations, and 0% schema description coverage, the description should handle all context. It misses the meaning of the 'monitor' parameter and fails to state the output format (e.g., base64, URL, path), making it incomplete for an agent to call correctly in multi-monitor or output-sensitive scenarios.

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%, so the description must compensate. It clearly defines region as 'x,y,w,h', scale as 0-1, and quality as 1-100, adding meaning to three of four parameters. It entirely omits the 'monitor' parameter, leaving it unexplained.

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 states a specific verb and resource: 'Capture the screen as an image'. 'For vision-capable models' further clarifies the intended use case, and the plain-image capture distinguishes it from OCR siblings like ocr_screen and window_capture_ocr.

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 phrase 'for vision-capable models' implies a use case, but there is no explicit guidance on when to use this tool versus alternatives like ocr_screen or window_capture_ocr. No exclusions or when-not-to-use conditions are provided.

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

Deploy Server

Other Tools