Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Tiartyos/mcp-window-screenshooterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/tiartyos/mcp-window-screenshooter/project-description)<a href="https://agentmods.dev/rules/tiartyos/mcp-window-screenshooter/project-description"><img src="https://agentmods.dev/badge/rules/tiartyos/mcp-window-screenshooter/project-description/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/tiartyos/mcp-window-screenshooter/project-description"><img src="https://agentmods.dev/badge/rules/tiartyos/mcp-window-screenshooter/project-description.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00961 | $0.00961 |
| Opus 5 | $0.00481 | $0.00481 |
| Sonnet 5 | $0.00192 | $0.00192 |
| Haiku 4.5 | $0.00096 | $0.00096 |
Grade A, and why
project-description scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Window Screenshooter MCP Server A cross-platform Model Context Protocol (MCP) server that enables AI agents to capture screenshots of specific application windows, kupo!
Overview Window Screenshooter is an MCP server built in Python that provides AI agents with the capability to take targeted screenshots of specific application windows across Windows, Linux, and macOS platforms. Unlike traditional screen capture solutions that only capture the entire screen, this server allows precise window-based capture for AI verification workflows, automated testing, and application monitoring.
Key Features:
🖼️ Window-Specific Capture: Target individual application windows by name or title
🌐 Cross-Platform Support: Works on Windows, Linux, and macOS with platform-optimized backends
🔧 MCP Integration: Seamless integration with AI agents through Model Context Protocol
📡 STDIO Transport: Uses standard input/output for reliable communication
⚡ Performance Optimized: Platform-specific implementations for maximum efficiency
Technical Architecture Cross-Platform Window Management Built on PyWinCtl, a robust cross-platform library that evolved from PyGetWindow to support:
Window enumeration and identification across all platforms
Multi-monitor setup compatibility
Window state management and control
Platform-Specific Capture Backends Windows Implementation:
Utilizes win32gui with BitBlt API for robust window capture
Can capture minimized, hidden, or overlapped windows
High-performance Graphics Capture API integration option
Linux Implementation:
Xlib-based window capture using native X11 protocols
Direct window buffer access for efficient capture
Support for Wayland environments where available
macOS Implementation:
Coordinate-based capture with PyWinCtl window positioning
Native macOS window server integration
Optimized for Retina displays
MCP Tool Integration The server exposes the following MCP tools:
capture_window Captures a screenshot of a specific window by title or identifier.
Parameters:
window_title (string): Exact or partial window title to match
output_path (string, optional): Save location for screenshot
format (string, optional): Image format (PNG, JPEG)
quality (int, optional): JPEG quality (1-100)
Returns: Base64-encoded image data or file path confirmation
list_windows Enumerates all available windows on the system.
Returns: Array of window objects with ID, title, position, and size information
get_window_info Retrieves detailed information about a specific window.
Parameters:
window_identifier (string): Window title or ID
Returns: Window metadata including position, size, visibility state, and process information
Use Cases AI Development Workflows:
Code Verification: AI takes Unity editor screenshots to verify game object placement
UI Testing: Capture application states during automated testing sequences
Documentation: Generate visual documentation of application interfaces
Debugging: Visual confirmation of application behavior changes
Automation Scenarios:
Quality Assurance: Screenshot comparison for regression testing
Process Monitoring: Capture application states for workflow verification
Training Data: Generate labeled screenshots for computer vision training
Installation & Setup bash
Clone the MCP server template
git clone https://github.com/sontallive/mcp-server-python-template cd mcp-server-python-template
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 187 lines · 961 tokens per session scan A 754c114918ee
project-description is a cursor rule published in the GitHub repository Tiartyos/mcp-window-screenshooter (0 stars, last pushed 1y ago), licensed MIT. It adds 961 tokens to every session, about $0.0048 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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