HuskyLens2MCP
Verified Safeby ronibandini
Overview
Provides a command-line interface to interact with a DFRobot HuskyLens 2 MCP Server, leveraging Google Gemini AI for visual reasoning and natural language processing of sensor data.
Installation
python HuskyMCPChat.pyEnvironment Variables
- GEMINI_API_KEY
- SERVER_URL
Security Notes
The script is a client and connects to a user-specified HuskyLens MCP server. Hardcoded placeholders for `GEMINI_API_KEY` and `SERVER_URL` require manual modification by the user, which is a minor security anti-pattern but acceptable for a local CLI utility. Input for LLM prompts (from HuskyLens sensor data and user queries) introduces inherent prompt injection risks, common in LLM applications. No `eval` or `exec` found. `os.system('cls')` is used for clearing the console, not a security risk.
Similar Servers
holoviz-mcp
Enables AI assistants to build interactive dashboards and data visualizations with HoloViz libraries like Panel, hvPlot, Lumen, and Datashader, by providing intelligent access to documentation, component information, and a display server.
reachy-mini-mcp
Control a Reachy Mini robot through an MCP or OpenAI-compatible API, enabling dynamic execution of robot movements, gestures, and conversational interactions.
agents-mcp-usage
This repository demonstrates the integration of a Model Context Protocol (MCP) server with various AI agent frameworks, showcasing agent communication and operation within a shared context.
mcp_server
This server template provides a foundation for building Model Context Protocol (MCP) servers to integrate with AI assistants and other MCP clients, offering tools for GitHub, Microsoft Graph, weather data, and JWT decoding.