The HowToCook - MCP Server is a project that transforms an AI assistant into a personal chef. Based on the HowToCook recipe data, it provides functions such as recipe query and meal recommendation for AI clients through the MCP protocol, solving the problem of 'what to eat today'.

Grigori is a desktop application that helps developers manage and organize programming specifications, architectural patterns, and development preferences through the MCP protocol, enabling AI programming assistants to access personalized coding contexts.

GitHub Copilot Memory Tool, designed for the new features of VS Code 2025. It allows Copilot to remember user preferences and work context through persistent memory, enhancing the personalized experience of the AI programming assistant.

A personal data aggregation center based on the MCP protocol, allowing AI assistants to access personal data from multiple platforms and providing a personalized interaction experience.

Cursor chat history analysis tool that allows AI assistants to read local chat data through the MCP protocol, providing personalized programming assistance and pattern analysis

A personal assistant AI agent based on the MCP protocol, providing functions such as calendar management, task tracking, email handling, and smart home control, which can be integrated into MCP clients like Claude for use.

A production-level MCP server that provides AI assistants with access to the Finnish Alko alcohol product catalog, including product search, inventory query, store information, and personalized recommendations.

This project implements a personal context management server based on the MCP protocol, which is used to store and update users' personalized data, enabling AI assistants to maintain memory across sessions and provide personalized services.

BeeMCP is an unofficial MCP server used to connect the data of Bee wearable devices with large - language models (such as Claude), enabling AI assistants to access and manipulate users' personal data, including conversations, fact records, to - do lists, and location history.

AutoMem MCP is an MCP client tool that provides persistent memory for AI assistants. By connecting to the AutoMem graph - vector memory service, MCP - compatible AI platforms such as Claude, Cursor, and GitHub Copilot can remember users' decisions, coding styles, and preferences across sessions and devices, achieving perfect memory and personalized interaction.

A Hexo blog RAG MCP server based on vector search that transforms a personal blog into a dedicated knowledge base for AI assistants, enabling semantic retrieval and enhanced answers.

What2Watch MCP is a service that provides real - time entertainment content discovery capabilities for AI assistants. It integrates program information from thousands of TV channels and streaming platforms and can provide personalized recommendations based on user preferences, mood, and time.

The Health & Fitness Coach MCP is an AI - driven comprehensive fitness tracking application, including a Web dashboard and an MCP server. It enables intelligent interaction between the AI assistant and fitness data through the Model Context Protocol, providing functions such as exercise recording, nutrition tracking, and personalized plan generation.

A lightweight MCP server that enables AI agents or MCP - compatible assistants to initiate and verify PID (Personal Identity Data) credential presentations through the OIDC4VP protocol, suitable for secure, QR - code - based wallet interactions.

MiniMe-MCP is an upgraded project for an AI development assistant. By creating a digital twin of the developer, it enables persistent memory and intelligent pattern recognition across projects. It solves the problem that traditional AI assistants lack memory and context understanding, provides personalized coding suggestions based on historical experience, supports multiple IDE tools, and can run locally to ensure data privacy.

Lark MCP is an AI assistant framework based on Feishu. It realizes function calls and message processing through reverse Feishu protocol, supports custom function registration and automatic matching calls. There's no need to configure a robot, and you can directly use your personal Feishu account as an AI assistant.