What is FlaUI-Screenreader-MCP?

61/100
Trust Score (C)
⚠️ Use Caution

FlaUI-Screenreader-MCP is a AI tool that A PoC implementation of a MCP server, enabling AI Agents to "see" UIA3 Automation Trees of a running program and do some basic interaction in order to support devs and QA during the creation of E2E UI. It has a Nerq Trust Score of 61/100 (C). 0 GitHub stars. Published by Rotbarsch. Last analyzed August 2026.

Why This Score

Trust & Safety Overview

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TRUST SCORE
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What FlaUI-Screenreader-MCP Does

FlaUI-Screenreader-MCP is a agent in the AI tool category. A PoC implementation of a MCP server, enabling AI Agents to "see" UIA3 Automation Trees of a running program and do some basic interaction in order to support devs and QA during the creation of E2E UI Tests.. It is published by Rotbarsch and is open source. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use FlaUI-Screenreader-MCP

FlaUI-Screenreader-MCP is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.

Details

AuthorRotbarsch
CategoryAI tool
LicenseMIT
Typeagent
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=flaui-screenreader-mcp

Setup guide · Full safety report · Production review · Is it safe?

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Frequently Asked Questions

What is FlaUI-Screenreader-MCP used for?
FlaUI-Screenreader-MCP is a AI tool tool. A PoC implementation of a MCP server, enabling AI Agents to "see" UIA3 Automation Trees of a running program and do some basic interaction in order to support devs and QA during the creation of E2E UI.
Is FlaUI-Screenreader-MCP free?
License: MIT. FlaUI-Screenreader-MCP has 0 GitHub stars.
Is FlaUI-Screenreader-MCP safe?
FlaUI-Screenreader-MCP has a Nerq Trust Score of 61/100 (C). Use with caution.
What are alternatives to FlaUI-Screenreader-MCP?
Top alternatives: openclaw, tensorflow, AutoGPT. See full comparison.

Last updated August 2026. Trust scores based on automated analysis of public data.

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