Provides persistent memory and context capabilities to AI agents for enhanced long-term retention and recall.
Sponsored
Akashic Context is an open-source Universal Memory & Context Engine designed to equip AI agents with long-term memory. It addresses the common limitation of AI agents forgetting past interactions by storing memories in human-readable Markdown files. This solution enables agents to remember conversations, decisions, and context across multiple sessions, making them more effective and capable. It integrates easily via the MCP Protocol, supporting various AI agent platforms.
Key Features
010 GitHub stars
02Stores memories in human-readable Markdown files (git-friendly)
03Ranks search results by relevance score
04Intelligently searches memories using BM25 keyword matching
05Chunks large memory files for efficient searching
06Integrates easily via MCP Protocol (n8n, Claude Desktop, Cursor compatible)
Use Cases
01Enabling AI agents to retain project details and decisions across development cycles
02Building AI systems that can learn and adapt over time by remembering past contexts
03Giving AI personal assistants persistent memory to recall user preferences and past interactions
