MemPalace/mempalace
MemPalace is an open-source, local-first AI memory system that stores and retrieves conversation history verbatim using semantic search, supporting pluggable backends like ChromaDB and integrating ...
Awesome MCP › Knowledge & Memory
MicrosoftDocs/mcp
The Microsoft Learn Docs MCP Server is a cloud-hosted service that implements the Model Context Protocol (MCP) to provide AI assistants with real-time access to official Microsoft documentation. This service enables AI systems like GitHub Copilot, Cursor, and others that support MCP to perform semantic searches and retrieve accurate, authoritative content from Microsoft Learn, Azure documentation, Microsoft 365 documentation, and other official Microsoft sources. The server uses advanced vector search technology to understand the context of queries and returns up to 10 high-quality content chunks, each with a maximum of 500 tokens, including article titles, URLs, and self-contained content excerpts. This ensures that AI assistants can ground their responses in the most relevant and up-to-date Microsoft documentation. The Microsoft Learn Docs MCP Server is accessible via a standardized remote MCP endpoint, allowing any compatible IDE, agent, or tool to connect programmatically. It supports multiple popular development environments and tools, including VS Code, Claude Desktop, Visual Studio, Cursor IDE, Roo Code, and Cline, with streamlined installation options and detailed guides for each. For legacy clients or local configurations, the server can be accessed through a proxy called mcp-remote. This project is currently in Public Preview, indicating that the implementation may evolve before general availability. The server is designed to enhance AI-assisted development workflows by providing seamless, real-time access to official Microsoft documentation, improving the accuracy and reliability of AI-generated responses. It is a key infrastructure component for integrating Microsoft documentation into AI tools via the Model Context Protocol, supporting semantic search and standardized data retrieval.
https://github.com/MicrosoftDocs/mcp
Also in Knowledge & Memory
siyuan-note/siyuan
SiYuan is a privacy-first, self-hosted personal knowledge management system featuring block-level referencing, Markdown WYSIWYG editing, and support for the Model Context Protocol (MCP).
topoteretes/cognee
Cognee is an open-source project that provides scalable and modular memory capabilities for AI agents using ECL pipelines, enabling efficient management and retrieval of past interactions and diverse data types.
vectorize-io/hindsight
Hindsight is an agent memory system designed to create smarter, learning AI agents by moving beyond simple conversation history recall to encompass a biomimetic storage architecture for long-term m...
screenpipe/screenpipe
Screenpipe is a local-first, AI-powered memory tool that records computer activity (screen, audio, accessibility tree) to provide a searchable, automated context for personal AI agents and users, i...
Olow304/memvid
Memvid is a video-based AI memory library that stores millions of text chunks in MP4 files with ultra-fast semantic search, eliminating the need for traditional databases and enabling portable, efficient AI memory management.
EverMind-AI/EverOS
EverOS is an open-source Python framework for self-evolving, portable, long-term memory for AI agents, supporting multimodal ingestion and local-first persistence with Markdown as the source of truth.
MemTensor/MemOS
MemOS is a Memory Operating System for LLMs and AI agents that unifies long-term memory management, offering a single API for structured, multi-modal memory with enterprise-grade optimizations, sig...