Screen Vision MCP Server

by avicuna

Overview Schema Source Related Servers Discussions Admin

Python

Local

capture_window

Capture a window by its title, with optional scaling, to obtain frame data as JSON.

Instructions

Capture a specific window by title.

Args: window_title: Title of the window to capture scale: Scale factor for resizing (default: 0.5)

Returns: JSON string with captured frame data or error

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": {
      "window_title": "<window_title>"
    },
    "name": "capture_window"
  }
}

Input Schema

Name	Required	Description	Default
`scale`	No
`window_title`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.4Jul 6, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only states that it captures a window and returns JSON, omitting details like permission needs, window findability, side effects, or error conditions beyond a generic 'error'.

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 brief and well-structured with Args and Returns sections. Every sentence contributes necessary information, though it could include more context without being verbose.

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?

With only 2 parameters, 0% schema coverage, no annotations, but an output schema present, the description provides the core functionality. However, it lacks explanatory context about use cases, prerequisites, or error handling, making it only minimally complete for an agent.

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?

The input schema has 0% description coverage, so the description must add value. It labels 'window_title' as 'Title of the window to capture' and 'scale' as 'Scale factor for resizing (default: 0.5).' This provides intent but is minimal; a higher score would require more detail like format constraints or behavior details.

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 'Capture a specific window by title,' specifying the verb (capture), resource (window), and qualification (by title). This distinguishes it from sibling tools like capture_screen (full screen) and capture_region (by coordinates).

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 is provided on when to use this tool versus alternatives such as capture_screen or capture_region. There is no discussion of prerequisites, window visibility requirements, or conditions that might make this tool unsuitable.

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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