Hello everyone! 
I built MemorizedMCP, an MCP Server for AI agents that adds:
* Persistent memory across sessions
* Built-in document store (add, index, search, retrieve)
* Document operations: chunking, embedding, tagging, and querying
* Tool orchestration for multi-step tasks
* Lightweight, extensible design
It’s …
A high-performance hybrid memory system for AI agents built on the Model Context Protocol (MCP). MemorizedMCP combines knowledge graphs, vector embeddings, full-text search, and documentary memory to provide intelligent, context-aware information storage and retrieval.
Repo: https://github.com/PerkyZZ999/MemorizedMCP
I use it regularly with my project on Cursor so I think it would be time to share it with the world and have other people use it … So if you wanna try go to the repo and follow the instructions 
I’d love feedback, issues, and PRs—especially on the document features and real-world use cases!
PerkyZZ - PerkyZZ999 (Charles Wilkin) · GitHub .
Have a nice day to everyone