Mobile Mcp
MCP Server for Android/iOS application and device automation, development and app scraping. Simulator/Emulator/Physical devices like iPhone, Google Pixel, Samsung supported.
Install Mobile Mcp
Install instructions vary — visit the GitHub repository for the latest install command. Most MCP servers follow one of three patterns: npx -y <package> for Node, uvx <package> for Python, or docker run <image> for containerized servers.
Use Mobile Mcp with Claude Code
Once the server is on your machine, register it with Claude Code so the agent can call it like any other tool. The general pattern is:
claude mcp add mobile-next-mobile-mcp -- <install-command>After it's registered, run claude and ask anything that requires Mobile Mcp. Claude Code will negotiate the MCP handshake and surface the server's tools, prompts, and resources to the model automatically. See our Claude Code MCP guide for environment variables, scope flags, and credential handling.
What this server is for
Mobile Mcp sits in the developer tools category. It's community-maintained — check the repo's last-commit date and open issues before depending on it in production. The full description from the source list:
MCP Server for Android/iOS application and device automation, development and app scraping. Simulator/Emulator/Physical devices like iPhone, Google Pixel, Samsung supported.
FAQ
Is Mobile Mcp free?
Yes — every MCP server in the ClawHire directory is open-source or freely available. Some servers proxy to paid APIs (you supply your own keys), but the server itself is free.
Does it work with Claude Desktop / Cursor / Windsurf?
If a client speaks the Model Context Protocol, it can use this server. The transport (stdio vs SSE vs HTTP) needs to match what the client supports, but the server itself is client-agnostic.
How do I report a bug or contribute?
Open an issue or PR on the GitHub repository.
More developer tools servers
MCP server to talk to your [Opik](https://github.com/comet-ml/opik) cloud or open-source instance to query and analyze LLM traces, metrics and observability.
AI-powered developer assistant that enables advanced research, analysis and discovery and code generation across GitHub and NPM realms in realtime.
APISIX Model Context Protocol (MCP) server is used to bridge large language models (LLMs) with the APISIX Admin API, supporting querying and managing all resources in [Apache APISIX](https://github.com/apache/apisix).
Run and manage docker containers, docker compose, and logs
Excel manipulation including data reading/writing, worksheet management, formatting, charts, and pivot table
Analyzes your codebase identifying important files based on dependency relationships. Generates diagrams and importance scores per file, helping AI assistants understand the codebase. Automatically parses popular programming languages, Python, Lua, C, C++, Rust, Zig.