Local MCP Tools Collection

A small collection of Model Context Protocol (MCP) tools, build for local LLMs. One venv, many options.

Why is exists?

The MCP server now is mostly scattered. There is no simple tool-pack. We need to set it up per-tool. This tool pack is targeted for local convenient use. I will expand the collections through time. Make LocalLLMs more powerful yet simplier.

Features

MCP json Configuration file generation: Run main.py and go through the wizard to complete the generation
One venv for multiple MCP servers

MCP Servers

Web Search: Use duckduckgo as search engine, fetch and summarize top results
Python SandBox: Allow Agents to run python, use numpy and sympy, good for math
Longterm-Memory: For Agents to memories things for longterm use.

Notes

It is default using stdio, You can set it to http in GlobalConfig
In python-sandbox.py, exec() function is used to allow agent execute python scripts, keep an eye on Agents.

Requirements

Python >= 3.13
Managed with uv

Install

Using uv:

uv sync

Run the MCP Server

python python-sandbox.py

The server communicates over stdio (FastMCP). Point your MCP-compatible client at the executable command above.

Tool Usage Examples

Run main.py for json configuration auto generation. And you will get something like this:

{
  "mcpServers": {
    "memory": {
      "command": "E:\\LMStudio\\mcp\\lmstudio-toolpack\\.venv\\Scripts\\python.exe",
      "args": [
        "E:\\LMStudio\\mcp\\lmstudio-toolpack\\MCPs\\Memory.py"
      ]
    },
    "python-sandbox": {
      "command": "E:\\LMStudio\\mcp\\lmstudio-toolpack\\.venv\\Scripts\\python.exe",
      "args": [
        "E:\\LMStudio\\mcp\\lmstudio-toolpack\\MCPs\\python-sandbox.py"
      ]
    },
    "websearch": {
      "command": "E:\\LMStudio\\mcp\\lmstudio-toolpack\\.venv\\Scripts\\python.exe",
      "args": [
        "E:\\LMStudio\\mcp\\lmstudio-toolpack\\MCPs\\WebSearch.py"
      ]
    }
  }
}

Change the name if you needed

Another Idea

If you choose using http. You can use 1mcp to unify them all. And run it on a remote server. Eg. Connect a Resberry PI to TailScale and set it up remotely.

LMStudio Toolpack