Screeny▌
by rohanrav
Screeny is a privacy-focused mac application MCP server for secure, user-approved window screenshots on macOS.
Privacy-focused macOS MCP server for secure, user-approved window screenshots
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / AI agents debugging macOS applications
- / Automating visual testing workflows
- / Development tasks requiring screen context
capabilities
- / Take screenshots of pre-approved macOS windows
- / List all approved application windows
- / Capture windows in background without focus
- / Process screenshots locally without external connections
what it does
Captures screenshots of specific macOS application windows for AI agents, requiring explicit user approval for each window before it can be accessed.
about
Screeny is a community-built MCP server published by rohanrav that provides AI assistants with tools and capabilities via the Model Context Protocol. Screeny is a privacy-focused mac application MCP server for secure, user-approved window screenshots on macOS. It is categorized under developer tools.
how to install
You can install Screeny in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Screeny is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme

Screeny MCP Server: Privacy first macOS Screenshots for AI Agents
A privacy-first, macOS-only MCP server that enables AI agents to capture screenshots of pre-approved application windows, providing secure visual context for development and debugging tasks.
[!IMPORTANT] Requires Screen Capture permission + Window Approval Setup - see instructions below.
🔒 Privacy-First Design
Unlike other screenshot tools, Screeny requires explicit user approval for each window before it can be captured:
- Window approval system - Only pre-approved windows can be captured (approved during setup)
- User-controlled access - You decide exactly which windows are accessible
- Non-intrusive capture - Screenshots taken in background without changing window focus or interrupting your workflow
- No external connections - Screeny runs entirely on your device, screenshots are deleted immediately after use
Available Tools
-
listWindows- Lists all approved application windows available for screenshot capture.- Only shows user approved windows
-
takeScreenshot- Captures a screenshot of a specific window by its ID.- Captures windows in background - no need to bring window to front, but cannot capture minimized windows
- Provides actual pixel data - full-fidelity image, not OCR or text extraction
- JPEG compression with configurable cap - screenshots are always JPEG-compressed with a base64 payload cap (default preset: Medium / 250KB), configurable and clamped to 100–900KB
Resources
screeny://info- Server information and configuration details
Configuration
Claude Desktop
- Open Claude settings → Developer → Edit Config
- Add configuration
- Restart Claude Desktop after saving config
First install with: pipx install mcp-server-screeny
{
"mcpServers": {
"screeny": {
"command": "mcp-server-screeny",
"args": []
}
}
}
</details> <details> <summary><strong>Using uvx</strong></summary>Note: If you get an
ENOENTerror, replace"mcp-server-screeny"with the full path to the executable (find it withwhich mcp-server-screenyin your terminal).
{
"mcpServers": {
"screeny": {
"command": "uvx",
"args": ["mcp-server-screeny"]
}
}
}
</details>Note: If you get a "spawn uvx ENOENT" error, replace
"uvx"with the full path to uvx:which uvx # Find your uvx pathThen use that full path in the config (e.g.,
"/opt/homebrew/bin/uvx").
Cursor
- Open Cursor settings → Tools & Integrations → MCP Tools
- Add configuration
- Restart Cursor after saving config
First install with: pipx install mcp-server-screeny
{
"mcpServers": {
"screeny": {
"command": "mcp-server-screeny",
"args": []
}
}
}
</details> <details> <summary><strong>Using uvx</strong></summary>Note: If you get an
ENOENTerror, replace"mcp-server-screeny"with the full path to the executable (find it withwhich mcp-server-screenyin your terminal).
{
"mcpServers": {
"screeny": {
"command": "uvx",
"args": ["mcp-server-screeny"]
}
}
}
</details>Note: If you get a "spawn uvx ENOENT" error, replace
"uvx"with the full path to uvx:which uvx # Find your uvx pathThen use that full path in the config (e.g.,
"/opt/homebrew/bin/uvx").
[!NOTE] > Cursor MCP host
- Cursor auto context summarization can trigger looping tool calls (repeated screenshots).
- If this happens, lower the KB cap (use a smaller preset) or choose a model with a larger context window.
Setup
1. Grant Screen Capture Permission (Required)
Important: Grant permission before running window approval.
Note: You need to grant Screen Capture permission to BOTH:
- Your Terminal application (Terminal.app, iTerm2, etc.) - Required for running setup (can be disabled after)
- Your MCP host (Claude Desktop, Cursor) - Required for taking screenshots
To add them:
- Open System Settings > Privacy & Security > Screen & System Audio Recording
- Click the "+" button
- Add your Terminal application AND your MCP host application
- Restart both applications after granting permissions
2. Window Approval (Required)
After configuring your MCP client above, approve which windows can be captured.
<details> <summary><strong>If using pipx</strong></summary># Interactive approval
mcp-server-screeny --setup
# Auto-approve all current windows
mcp-server-screeny --setup --allow-all
</details>
<details>
<summary><strong>If using uvx</strong></summary>
# Interactive approval
uvx mcp-server-screeny --setup
# Auto-approve all current windows
uvx mcp-server-screeny --setup --allow-all
</details>
Approvals are saved to ~/.screeny/approved_windows.json. Re-run setup when you want to update the list of approved windows.
Advanced Options (Optional)
During setup, you can configure the screenshot size preset (affects stability and clarity):
- Tiny (50KB) — most stable; fine text will blur
- Small (100KB) — recommended default; balanced clarity and stability
- Medium (250KB) — more detail; may be slower and heavier
- Large (500KB) — high detail; may trigger client summarization
- XL (750KB) — maximum detail; most error-prone
Your choice is saved in ~/.screeny/config.json as max_b64_kb. You can also override via the SCREENY_MAX_B64_KB environment variable. The active cap is clamped to 100–900KB.
Security & Privacy
- Only user-approved windows can be captured
- All processing stays local on your machine
- Screenshots are temporary and deleted immediately after use
Troubleshooting
Permission Issues
# Test window detection and permissions
mcp-server-screeny --debug
# Re-run setup if windows changed
mcp-server-screeny --setup
Common Issues
"spawn uvx ENOENT" error
- Solution: Use the full path to uvx in your MCP config instead of just
"uvx" - Find path with:
which uvx - Example:
"/opt/homebrew/bin/uvx"or"/usr/local/bin/uvx"
"No approved windows found"
- Solution: Run
mcp-server-screeny --setupfirst (oruvx mcp-server-screeny --setupif using uvx)
"Screen Recording permission required" or "No windows found"
- Solution: Grant Screen Recording permission in System Settings > Privacy & Security > Screen & System Audio Recording
- Click "+" button and manually add your MCP host (Claude Desktop, Cursor, etc.)
- Restart your MCP host application after granting permissions
- Try running setup again after granting permissions
Contributing
Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements.
This is my first MCP project - if you encounter any bugs, please open an issue and I'll do my best to fix them!
<details> <summary><strong>Why I Built This</strong></summary>I created this tool to streamline my mobile development workflow. I was tired of manually taking screenshots repeatedly to describe UI issues. With Screeny, Cursor can directly capture screenshots of my iOS simulator and iterate on the design in a loop. I'm excited to see how others will use this!
</details>Requirements
- Python 3.10+
- macOS
- Screen Capture permission
License
MIT License
FAQ
- What is the Screeny MCP server?
- Screeny is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Screeny?
- This profile displays 31 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★31 reviews- ★★★★★Dhruvi Jain· Dec 8, 2024
Strong directory entry: Screeny surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Hana Malhotra· Dec 8, 2024
According to our notes, Screeny benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Oshnikdeep· Nov 27, 2024
Screeny is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Anaya Ramirez· Nov 27, 2024
We wired Screeny into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ganesh Mohane· Oct 18, 2024
We evaluated Screeny against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Anika Mensah· Oct 18, 2024
Screeny is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Fatima Choi· Sep 9, 2024
I recommend Screeny for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★William Verma· Sep 1, 2024
Strong directory entry: Screeny surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Noah Liu· Aug 28, 2024
Strong directory entry: Screeny surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★William Menon· Aug 20, 2024
I recommend Screeny for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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