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Merge pull request #12268 from iksnerd/add-adb-mcp
Add iksnerd/adb-mcp under Developer Tools 🤖🤖🤖
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@@ -1363,6 +1363,7 @@ Tools and integrations that enhance the development workflow and environment man
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- [icohangar-ops/codesentinel](https://github.com/icohangar-ops/codesentinel) [](https://glama.ai/mcp/servers/icohangar-ops/codesentinel) 📇 🏠 🍎 🪟 🐧 - Dead code, circular dependencies, coupling, and architectural drift as MCP tools. Official MCP Registry: `io.github.icohangar-ops/codesentinel-mcp`. `npx -y @cubiczan/codesentinel-mcp`
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- [idosal/git-mcp](https://github.com/idosal/git-mcp) 📇 ☁️ - [gitmcp.io](https://gitmcp.io/) is a generic remote MCP server to connect to ANY [GitHub](https://www.github.com) repository or project for documentation
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- [IgorGanapolsky/ThumbGate](https://github.com/IgorGanapolsky/ThumbGate) [](https://glama.ai/mcp/servers/IgorGanapolsky/ThumbGate) 📇 🏠 - MCP server that blocks AI coding agents from repeating mistakes — turns thumbs-up/down feedback into enforced pre-action gates via PreToolUse hooks. Install: `npx thumbgate`.
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- [iksnerd/adb-mcp](https://github.com/iksnerd/adb-mcp) [](https://glama.ai/mcp/servers/iksnerd/adb-mcp) 🏎️ 🏠 🍎 🪟 🐧 - Drive an Android emulator or device over adb: screenshots, `describe_ui` returning each element's center in true device pixels, tap/swipe/type, app lifecycle, permissions and deep links, logcat, screen recording, and Gradle builds with unit and instrumented tests.
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- [IlyaGulya/gradle-mcp-server](https://github.com/IlyaGulya/gradle-mcp-server) 🏠 - Gradle integration using the Gradle Tooling API to inspect projects, execute tasks, and run tests with per-test result reporting
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- [imatza-rh/mcp-zuul](https://github.com/imatza-rh/mcp-zuul) [](https://glama.ai/mcp/servers/imatza-rh/mcp-zuul) 🐍 ☁️ - Zuul CI integration with 14 tools for build failure analysis, log search, pipeline status, and job configuration.
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- [InditexTech/mcp-server-simulator-ios-idb](https://github.com/InditexTech/mcp-server-simulator-ios-idb) 📇 🏠 🍎 - A Model Context Protocol (MCP) server that enables LLMs to interact with iOS simulators (iPhone, iPad, etc.) through natural language commands.
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