Pref Editor (Android)▌
by charlesmuchene
Pref Editor (Android) lets you read, modify, and manage app preferences on Android via ADB for debugging and automation.
Integrates with Android devices through ADB connectivity to read, modify, add, and delete SharedPreferences and DataStore preference files for debugging app preferences, automating testing workflows, and managing app configuration data.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Android developers debugging app preferences
- / QA engineers testing different app configurations
- / Automating preference changes in CI/CD pipelines
capabilities
- / List connected Android devices
- / Browse installed apps and preference files
- / Read all preferences from app files
- / Add new preferences with specified types
- / Modify existing preference values
- / Delete unwanted preferences
what it does
Connects to Android devices via ADB to read and modify app SharedPreferences and DataStore files using natural language commands.
about
Pref Editor (Android) is a community-built MCP server published by charlesmuchene that provides AI assistants with tools and capabilities via the Model Context Protocol. Pref Editor (Android) lets you read, modify, and manage app preferences on Android via ADB for debugging and automation. It is categorized under developer tools. This server exposes 7 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Pref Editor (Android) 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
Apache-2.0
Pref Editor (Android) is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Android Preference Editor MCP Server
<a href="https://glama.ai/mcp/servers/@charlesmuchene/pref-editor-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@charlesmuchene/pref-editor-mcp-server/badge" alt="Pref-Editor MCP Server"/> </a>Overview
Unlock the power of natural language for Android app development with the Android Preference Editor MCP Server. Effortlessly edit user preferences in real time using simple, conversational commands—no manual file editing required! Built on the robust Android Preference Editor library, this server seamlessly connects with MCP (Model Context Protocol) clients to supercharge your AI-driven workflows.
Just tell the MCP server what you want to do, for example:
- “Toggle the isVisited user preference”
- “Turn off the onboarding guide”
- “List all the user preference values”
- "Create a timestamp preference with the current epoch time"
Experience a smarter, faster way to manage Android preferences—just ask!
Available Tools
| Name | Description |
|---|---|
| change_preference | Changes the value of an existing preference |
| delete_preference | Delete an existing preference |
| add_preference | Adds a new preference given the name, value, and type |
| read_preferences | Reads all user preferences in a file |
| devices | Lists connected Android devices |
| list_apps | Lists apps installed on the device |
| list_files | Lists preference files for an app |
Demo
| Toggle a user preference | Available tools | Add a preference |
|---|---|---|
![]() | ![]() | ![]() |
See more demos in the demo screenshots directory
Requirements
- Android adb (
v1.0.41+) - Node.js 14+ or Docker
Integrations
This server is available in the Docker MCP Catalog. Enable the Pref Editor server in Docker desktop's MCP toolkit and you'll have access to all the available tools.
Android Studio
Assumes an MCP compatible client is installed.
Add the following configuration to the MCP server config file. For example, for the GitHub Copilot IntelliJ Plugin, the config file is ~/.config/github-copilot/intellij/mcp.json.
Docker
{
"servers": {
"pref-editor": {
"command": "docker",
"args": ["run", "-i", "--rm", "charlesmuchene/pref-editor-mcp-server"]
}
}
}
npx
{
"servers": {
"pref-editor": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@charlesmuchene/pref-editor-mcp-server"]
}
}
}
Claude Desktop
Add this server to the /Users/<username>/Library/Application Support/Claude/claude_desktop_config.json configuration file.
Docker
{
"mcpServers": {
"pref-editor": {
"command": "docker",
"args": ["run", "-i", "--rm", "charlesmuchene/pref-editor-mcp-server"]
}
}
}
npx
{
"mcpServers": {
"pref-editor": {
"command": "npx",
"args": ["-y", "@charlesmuchene/pref-editor-mcp-server"]
}
}
}
You can troubleshoot problems by tailing the log file:
tail -f ~/Library/Logs/Claude/mcp-server-pref-editor.log
VS Code
To use the server with VS Code, you need to:
- Add the MCP Server configuration to your
mcp.jsonorsettings.json:
.vscode/mcp.json
{
"servers": {
"pref-editor": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@charlesmuchene/pref-editor-mcp-server"]
}
}
}
~/Library/Application Support/Code/User/settings.json
{
"mcp": {
"pref-editor": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@charlesmuchene/pref-editor-mcp-server"]
}
}
}
For more information, see the VS Code documentation.
Building Locally
Refer to DEV.md for instructions on how to build this project.
Testing
You can use the MCP Inspector for visual debugging of this MCP Server.
npx @modelcontextprotocol/inspector npm run start
License
See LICENSE
Contact
For questions or support, reach out via GitHub Issues.
Contributing
We welcome contributions from the community! 🎉
First-time contributors: Please start by reading our CONTRIBUTING.md guide, which covers:
- PR requirements and title format
- Development setup and workflow
- Code quality standards
- License information
For detailed development instructions, see DEV.md.
FAQ
- What is the Pref Editor (Android) MCP server?
- Pref Editor (Android) 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 Pref Editor (Android)?
- This profile displays 54 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 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
4.6★★★★★54 reviews- ★★★★★Aanya Ramirez· Dec 28, 2024
Pref Editor (Android) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Mia Sharma· Dec 16, 2024
According to our notes, Pref Editor (Android) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Chaitanya Patil· Dec 12, 2024
We evaluated Pref Editor (Android) against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kabir Mensah· Dec 12, 2024
Pref Editor (Android) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Henry Srinivasan· Nov 19, 2024
Pref Editor (Android) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Kabir Abbas· Nov 7, 2024
I recommend Pref Editor (Android) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Piyush G· Nov 3, 2024
Useful MCP listing: Pref Editor (Android) is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Kabir Gill· Nov 3, 2024
Pref Editor (Android) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Kabir White· Oct 26, 2024
Strong directory entry: Pref Editor (Android) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Shikha Mishra· Oct 22, 2024
Pref Editor (Android) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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