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Lmstudio Toolpack

The Local MCP Tools Collection aims to simplify the integration of multi - functional tools for local large language models, supporting multiple MCP servers through a single virtual environment, including web search, Python sandbox, and long - term memory functions.
Artificial intelligence chatbotsDeveloper tools#Local Tools#MCP Integration#Python Sandbox#Web Search.Python
2.5 points
5.2K
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Overview

Installation

Tools List

Content Details

Alternatives

What is the Local MCP Tools Collection?

This is a toolkit designed specifically for local large language models (LLMs), built based on the Model Context Protocol (MCP) standard. It enables your local AI assistant to access capabilities such as web search, running Python code, and saving long - term memory, just like installing a set of practical extension plugins for the AI assistant.

How to use this toolkit?

You only need to run a simple configuration wizard, which will automatically generate the MCP configuration file. Then add this configuration file to your LLM client (such as LM Studio), and your AI assistant can immediately use all the tools. The whole process is as simple as installing a mobile app.

Use cases

Suitable for users who want to enhance the capabilities of their AI assistants in a local environment, such as those who need the AI assistant to search for the latest information, perform mathematical calculations, write and test code, or remember important conversation content for later reference.

Main Features

Web Search
Use the DuckDuckGo search engine to obtain and summarize the latest web information. The AI assistant can search for any topic and obtain real - time information.
Python Sandbox
A secure Python code execution environment that supports mathematical libraries such as numpy and sympy. The AI assistant can run Python code, perform mathematical calculations, and conduct data analysis.
Long - Term Memory
Provides memory storage functionality for the AI assistant, which can remember important conversation content, user preferences, and key information, and recall them in subsequent conversations.
Automatic Configuration Generation
Provides a user - friendly configuration wizard that automatically generates the MCP configuration file without the need to manually write complex configuration code.
Unified Virtual Environment
All tools share the same Python virtual environment, simplifying dependency management and the installation process.
Advantages
Ready to use: The configuration wizard makes the setup process very simple.
Comprehensive functionality: Covers core needs such as search, calculation, and memory.
Local operation: All tools are executed locally to protect privacy.
Unified management: One virtual environment manages all tool dependencies.
Flexible deployment: Supports deployment on local and remote servers.
Limitations
Requires Python 3.13 or higher.
The Python sandbox function needs to be used with caution to avoid running insecure code.
Web search depends on the availability of the DuckDuckGo API.
Requires basic command - line operation knowledge.

How to Use

Installation Preparation
Ensure that your system has Python 3.13 or higher installed. It is recommended to use the uv package manager for installation.
Run the Configuration Wizard
Run the main.py file and follow the wizard's prompts to complete the configuration. The wizard will ask you which tools you need to enable.
Get the Configuration File
The wizard will generate an MCP configuration file (usually in JSON format). Copy the contents of this file.
Configure the LLM Client
Paste the contents of the generated configuration file into the MCP configuration section of your LLM client (such as LM Studio).
Start Using
Restart your LLM client, and now your AI assistant can use all the tools!

Usage Examples

Research and Learning
When you are learning new knowledge, you can ask the AI assistant to search for relevant latest materials and use Python to calculate relevant data.
Mathematical Calculation
When you need to solve complex mathematical problems, the AI assistant can directly run Python code for calculation.
Personal Assistant
Ask the AI assistant to remember your schedule, important matters, or personal preferences.

Frequently Asked Questions

Do I need programming knowledge to use this toolkit?
Is the Python sandbox safe?
Which LLM clients are supported?
Where is the data stored?
How to add new tools?

Related Resources

MCP Protocol Official Documentation
The official technical specification of the Model Context Protocol
GitHub Repository
The source code and latest version of this toolkit
LM Studio Official Website
A popular local LLM running platform
uv Package Manager
A fast Python package manager and installation tool

Installation

Copy the following command to your Client for configuration
{
  "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"
      ]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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