LMStudio Toolpack
Provides web search with DuckDuckGo and concurrent page fetching, sandboxed Python execution with NumPy and SymPy for mathematical computations, and persistent markdown-based memory storage for long-term information recall across conversations.
About
Built by Zihao FU using FastMCP and Python 3.13+, this toolpack combines three specialized tools designed for local LLM environments. It includes a web search tool that uses DuckDuckGo with concurrent page fetching and extractive summarization, a sandboxed Python execution environment with NumPy and SymPy for mathematical computations, and a persistent memory system that stores information in markdown format for long-term recall. The implementation emphasizes local operation without external API dependencies, making it valuable for users running local language models who need web research capabilities, mathematical problem-solving tools, and persistent memory across conversations.
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