Lipsky Memory

Lipsky Memory

Lipsky Memory MCP is a model context protocol server for managing project memory and context.

Knowledge management and memory Developer tools #Project memory #Context management #Relationship tracking #Persistence

rating : 2 points

downloads : 6.2K

update time : 2025-04-28

What is Lipsky Memory MCP?

Lipsky Memory MCP is a server for managing and storing project memory and context. It persists data through the Turso database, supports transaction processing, and can track relationships between entities.

How to use Lipsky Memory MCP?

Users can connect to the database by setting environment variables (such as LIBSQL_URL and LIBSQL_AUTH_TOKEN), and then execute relevant commands to manage project memory and context.

Applicable scenarios

Suitable for developers or teams who need to save project memory for a long time, track relationships between entities, and maintain context.

Main features

Project memory management

Allows users to create, edit, and delete project memory.

Entity and relationship tracking

Can record entities and their relationships for subsequent analysis.

Memory persistence

Utilizes the Turso database to ensure data security and persistence.

Transaction support

Provides a transaction mechanism to ensure operation consistency.

Advantages

Easy to use, no complex configuration required to get started quickly.

Powerful persistence ability to ensure data will not be lost.

Supports transactions to guarantee data integrity.

Limitations

There may be connection issues in the HyperChat environment (being fixed).

Limited performance in processing large-scale data.

How to use

Install dependencies

Ensure that the required software packages and drivers supporting the Turso database are installed.

Configure environment variables

Set LIBSQL_URL and LIBSQL_AUTH_TOKEN as database connection information.

Start the server

Run the command to start the Lipsky Memory MCP server.

Usage examples

Add a new project

Demonstrate how to add a new project to the system.

List entities in a project

Show how to get all entities of a specific project.

Frequently Asked Questions

How to solve the connection failure problem?

Can data be imported in batches?

Related resources

Official documentation

Detailed user manuals and technical guides.

GitHub code repository

Open-source code repository.

Video tutorial

Quick-start video.

Gitlab MCP Server

The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.

A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.

Duckduckgo MCP Server

The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.

Markdownify MCP

Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.

UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.

Figma Context MCP

Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.

Minimax MCP Server

The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.

Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.

AIBase

Zhiqi Future, Your AI Solution Think Tank

English 简体中文繁體中文にほんご

© 2025AIBase