VOOZH about

URL: https://glama.ai/mcp/servers/integrations/arduino

⇱ Arduino | Glama

  • Why this server?

    Enables routing and execution of hardware-related tasks on nodes equipped with Arduino connectivity and capabilities.

    A
    license
    A
    quality
    C
    maintenance
    Enables cluster-aware command execution and automatic task routing across distributed nodes based on system load, architecture, and OS requirements. It supports parallel execution, remote node management via SSH, and dynamic load balancing for agentic workflows.
    Last updated
    4
    MIT

  • Why this server?

    Allows AI assistants to understand and navigate Arduino firmware codebases by indexing them via compile_commands.json.

    A
    license
    A
    quality
    A
    maintenance
    Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.
    Last updated
    21
    MIT

  • Why this server?

    Allows AI assistants to control Arduino hardware: detect boards, compile and upload sketches, monitor serial, and run safety checks.

    A
    license
    A
    quality
    C
    maintenance
    Enables AI assistants to compile, upload, and monitor Arduino boards via natural language, with electrical safety checks and dependency management.
    Last updated
    21
    84
    13
    MIT

  • Why this server?

    Enables Arduino devices to query the memory mesh as hardware agents.

    A
    license
    A
    quality
    C
    maintenance
    A universal, local-first MCP hub that indexes personal files (documents, code, etc.) and provides private semantic search via hybrid dense+BM25 retrieval, enabling agents like Claude Desktop to query your data without sending it to the cloud.
    Last updated
    17
    5
    MIT

  • Why this server?

    Connects with ESP8266 devices through Arduino IDE, providing device management capabilities for NodeMCU devices including monitoring, configuration, and command execution.

    A
    license
    C
    quality
    D
    maintenance
    A service for managing ESP8266/NodeMCU IoT devices that provides both REST/WebSocket APIs and implements the Model Context Protocol for AI assistant integration.
    Last updated
    4
    1
    MIT

  • Why this server?

    Provides tools for interacting with Arduino CLI, enabling AI agents to manage boards, install cores and libraries, create, compile, and upload sketches, monitor serial output, and convert images to C arrays for displays.

    A
    license
    C
    quality
    D
    maintenance
    A comprehensive Model Context Protocol (MCP) server for Arduino CLI interactions, built with FastMCP. This server enables AI agents to seamlessly interact with Arduino CLI for development, debugging, code verification, and more.
    Last updated
    16
    2
    MIT

  • Why this server?

    Manages ESP8266/NodeMCU IoT devices that use Arduino IDE with ESP8266 support, allowing for device monitoring, remote command execution, and configuration updates.

    A
    license
    C
    quality
    D
    maintenance
    A Model Context Protocol service that enables remote management and control of NodeMCU/ESP8266 IoT devices with AI assistant integration through Claude Desktop.
    Last updated
    4
    1
    MIT

  • Why this server?

    Allows AI agents to discover, connect to, and interact with Arduino BLE devices for reading sensor data, sending commands, and subscribing to notifications.

    A
    license
    -
    quality
    B
    maintenance
    A stateful Bluetooth Low Energy (BLE) MCP server that enables AI agents to scan, connect, read/write characteristics, and subscribe to notifications on BLE devices.
    Last updated
    13
    MIT

  • Why this server?

    Supports capturing frames from Arduino-based cameras including ESP32-CAM modules via MJPEG streams.

    A
    license
    -
    quality
    B
    maintenance
    Provides camera and vision tools for AI assistants to list available cameras, capture images from USB cameras, and save frames to disk for use with LLMs.
    Last updated
    4
    MIT