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X-PLUG/MobileAgent

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MobileAgent

MobileAgent is an LLM-powered mobile automation agent and framework designed to navigate mobile user interfaces and execute multi-step tasks. It functions as a device interface automation system that maps semantic commands to screen coordinates to perform input events across mobile operating systems.

The project operates as a cross-app workflow orchestrator, switching between native on-screen interface actions and external API tools to complete sophisticated operations. It includes a visual grounding system that analyzes screenshots and interface metadata to identify elements and validate the success of actions through a feedback loop.

As a long-horizon task planner, the agent decomposes complex high-level goals into sequential executable steps. This process is supported by hierarchical state tracking and memory to maintain progress across multi-step automation workflows.

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Features

  • Agentic LLM Frameworks - Provides a comprehensive framework for building autonomous agents that use LLMs to navigate and interact with mobile user interfaces.
  • GUI Task Automation - Executes end-to-end operations across mobile devices by identifying interface elements and performing grounding actions.
  • Agentic Workflow Automation - Uses intelligent agents to coordinate tasks and automate complex, stateful workflows.
  • Cross-Application Workflow Automation - Executes goals that require moving between different mobile applications and external tools.
  • Interface Grounding - Maps high-level instructions to specific screen coordinates and interface components for mobile interaction.
  • Semantic Action Mappings - Implements the translation of semantic LLM commands into precise mobile device input events.
  • Agentic Goal Decomposition - Uses LLMs to recursively break high-level objectives into actionable sub-tasks for mobile automation.
  • Task Planners - Implements logic to decompose high-level automation goals into a sequence of executable steps with progress tracking.
  • Task Planning Systems - Provides a framework for decomposing complex automation goals into actionable steps and coordinating execution.
  • Visual Grounding - Maps AI-generated intents to specific screen coordinates by analyzing screenshots and interface metadata.
  • Hierarchical State Tracking - Provides hierarchical memory to track progress across complex, multi-step automation workflows.
  • Device Interface Automation Frameworks - Provides a system for identifying on-screen elements and performing grounding actions to automate mobile operations.
  • Mobile Device Automation - Performs complex tasks on mobile devices by automatically identifying and interacting with UI elements.
  • Native Mobile Automation - Enables the execution of semantic commands as input events within native mobile application environments.
  • Cross-App Workflow Orchestration - Coordinates transitions between native on-screen actions and external API tools to complete complex operations.
  • Visual State - Validates action success by comparing resulting screenshots with expected outcomes in a feedback loop.
  • Hybrid Tool Orchestration - Coordinates the use of native mobile interface interactions and external API calls.
  • Tool-Use Orchestration - Interleaves reasoning with a choice between native interface actions and external tool execution.
  • Tool Orchestration - Dynamically invokes native interface actions and external software within automated workflows.
  • Planning - Maintains explicit plans and progress lists for long-running autonomous mobile automation tasks.
  • Hybrid Tool Dispatching - Dynamically routes requests between native on-screen actions and external API tools.
  • Agent Frameworks - Assistant family for mobile device operations.
  • Agent Lifecycle Management - Self-evolving mobile assistant for complex task automation.
  • AI Agents and Workflows - Multimodal agent framework for autonomous smartphone app control.
  • GUI Agents - Autonomous multimodal agent for mobile device interaction.
  • GUI and Computer Agents - Fundamental agents and critics for GUI automation and error diagnosis.
9,372 stars·941 forks·Python·MIT·45 views

Star history

Star history chart for x-plug/mobileagentStar history chart for x-plug/mobileagent

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does x-plug/mobileagent do?

MobileAgent is an LLM-powered mobile automation agent and framework designed to navigate mobile user interfaces and execute multi-step tasks. It functions as a device interface automation system that maps semantic commands to screen coordinates to perform input events across mobile operating systems.

What are the main features of x-plug/mobileagent?

The main features of x-plug/mobileagent are: Agentic LLM Frameworks, GUI Task Automation, Agentic Workflow Automation, Cross-Application Workflow Automation, Interface Grounding, Semantic Action Mappings, Agentic Goal Decomposition, Task Planners.

Which projects share features with x-plug/mobileagent?

Projects with overlapping indexed features include: bytedance/ui-tars — UI-TARS is an LLM GUI automation framework and multimodal action grounding system. It functions as a GUI agent… simular-ai/agent-s — Agent-S is a multimodal AI agent and LLM desktop automation framework designed to control operating systems through… significant-gravitas/auto-gpt — Auto-GPT is an autonomous agent framework that uses large language models to decompose complex goals and execute… yoheinakajima/babyagi — This is a framework for building autonomous agents that use large language models to plan, execute, and refine their… agentscope-ai/agentscope — Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a… qwenlm/qwen-agent — Qwen-Agent is a development framework for building autonomous software applications that leverage large language…

Projects sharing features with MobileAgent

These projects share indexed features with MobileAgent. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • bytedance/ui-tarsbytedance avatar

    bytedance/UI-TARS

    11,683View on GitHub↗

    UI-TARS is an LLM GUI automation framework and multimodal action grounding system. It functions as a GUI agent orchestrator and cross-platform device controller that uses large language models to interpret graphical interfaces and execute actions across desktop and mobile operating systems. The system translates model-generated coordinates into precise screen positions to interact with visual user interface elements. It employs a multimodal approach to interpret screen layouts and decomposes complex goals into multi-step trajectories through reasoning and error correction. The project provid

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  • simular-ai/agent-ssimular-ai avatar

    simular-ai/Agent-S

    11,855View on GitHub↗

    Agent-S is a multimodal AI agent and LLM desktop automation framework designed to control operating systems through graphical user interface interactions. It functions as a computer use interface, utilizing vision-language grounding to translate natural language goals into precise screen coordinates and system actions. The project differentiates itself by combining structured accessibility tree inspection with vision-based element localization. It manages cross-application workflows by mapping conceptual descriptions to physical pixels and simulating low-level keyboard and mouse events to mov

    Pythonagent-computer-interfaceai-agentscomputer-automation
    View on GitHub↗11,855
  • significant-gravitas/auto-gptSignificant-Gravitas avatar

    Significant-Gravitas/Auto-GPT

    184,987View on GitHub↗

    Auto-GPT is an autonomous agent framework that uses large language models to decompose complex goals and execute multi-step tasks without human intervention. It functions as a workflow automation tool that chains language model tasks and manages memory to achieve specific objectives. The project features a visual agent designer that allows users to define behaviors and goals by connecting functional blocks through a graphical interface. It employs a vector database memory system to recall information across different sessions and a sliding-window buffer for immediate short-term context. The

    Python
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  • yoheinakajima/babyagiyoheinakajima avatar

    yoheinakajima/babyagi

    22,309View on GitHub↗

    This is a framework for building autonomous agents that use large language models to plan, execute, and refine their own tasks. It functions as an autonomous task orchestrator and agent framework, utilizing a function registry to manage the code-based tools and plugins the agents use to achieve complex goals. The system is distinguished by its ability to perform autonomous code generation, where the agent analyzes requirements to write new reusable functions on the fly. It employs a recursive loop-based planning model to continuously update its goal list and refine its performance based on ex

    Python
    View on GitHub↗22,309
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