关键词 "Device compatibility" 的搜索结果， 共 20 条, 只显示前 480 条
MCP Server for Android Debug Bridge (ADB), enabling Claude to interact with Android devices.
An MCP server that provides control over Android devices via adb
Minecraft Bedrock Edition BDS-liked server for aarch64 devices like raspi
MCP server that enables AI Agents to use images and events from Safie camera devices
An Model Context Protocol (MCP) server that provides access to Hunter API functionality, allowing AI assistants to query information about internet-connected devices and services.
Model Context Protocol Server for Mobile Automation and Scraping (iOS, Android, Emulators, Simulators and Physical Devices)
SImple MCP server to manage your aranet4 device and local db.
🌐🔌 An MCP server that exposes real-time sensor data from IoT Realm devices—such as ESP32-based DHT11 clients—to LLMs via the Model Context Protocol. This enables AI agents to access, analyze, and act
This is a Model Context Protocol (MCP) server that provides access to the Shodan API. It allows you to programmatically query Shodan for information about devices, vulnerabilities, and more.
This project is a Node.js application designed for use with Claude Desktop. It simulates a CO2 sensor device and provides a JSON-RPC server to interact with the device. The application can run in both
A Python MCP Server for Paper Analytical Devices (PAD)
An Anthropic MCP server (with OpenAI Function calling compatibility) for the Coingecko Pro API
A Model Context Protocol (MCP) server for interacting with Home Assistant. This server provides tools to control and monitor your Home Assistant devices through MCP-enabled applications.
MCP Server for IOT Devices
Node.js/TypeScript MCP server for AWS Single Sign-On (SSO). Enables AI systems (LLMs) with tools to initiate SSO login (device auth flow), list accounts/roles, and securely execute AWS CLI commands us
An MCP server for Omi devices calling uber
This project is a Java-based UI automation framework that integrates with Appium and utilizes LLMs (like Claude) to drive intelligent test actions on mobile devices and simulators.
MCP server to let LLM take full control on your device by providing screen automation toolkit for controlling and interacting with graphical user interface
FaceAge是一款AI人脸识别扫描模型，它通过数万张患者照片和公共图像数据库进行训练，能够精准判断个人衰老迹象。 模型描述 FaceAge 深度学习流程包括两个阶段：面部定位和提取阶段，以及带有输出线性回归器的特征嵌入阶段，可提供生物年龄的连续估计。 第一阶段通过在照片中定位人脸并在其周围定义一个边界框来预处理输入数据。然后对图像进行裁剪、调整大小，并在所有 RGB 通道上对像
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