The Cursor10x MCP is a persistent multi-dimensional memory system for Cursor that enhances AI assistants with conversation context, project history, and code relationships across sessions.
-
Updated
May 7, 2025 - JavaScript
The Cursor10x MCP is a persistent multi-dimensional memory system for Cursor that enhances AI assistants with conversation context, project history, and code relationships across sessions.
DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.
Cursor10x is a comprehensive suite of tools that enhances the A.I. agent's capabilities within the Cursor IDE, providing persistent memory across sessions, standardized task management, and enforced best practices through cursor rules.
Simple standalone MCP server giving Claude the ability to remember your conversations and learn from them over time.
MCP server that execute applescript giving you full control of your Mac
A lightweight MCP server that integrates with Apple Notes to create a personal memory system for AI. Easily recall and save information from your Mac using simple AppleScript commands. Compatible with all macOS versions with minimal setup requirements.
LangGraph Typescript Agents Notebooks: email, human in the loop, memory
AI agent that controls computer with OS-level tools, MCP compatible, works with any model
Excuse me sir? Did you order Special Sauce with that Agentic workflow?
This repository introduces the Letta framework, empowering developers to build LLM-based agents with long-term, persistent memory and advanced reasoning capabilities. It leverages concepts from MemGPT to optimize context usage and enable multi-agent collaboration for real-world applications like research, HR, and task management.
This project is a concept demonstration of a layered memory system for Large Language Models. It includes a CLI chatbot and an AI playing Zork I with 'FROTZ' as examples. The true value lies in the memory_handle.py module, designed for easy integration into any Python project requiring LLM memory management (AI agents, games, etc.).
The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).
DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.
AI-powered assistant that indexes Google Drive files to a vector store on upload and answers user queries based on the content.
Add a description, image, and links to the agent-memory topic page so that developers can more easily learn about it.
To associate your repository with the agent-memory topic, visit your repo's landing page and select "manage topics."