An MCP server offering persistent, semantic memory storage with RAG features using DuckDB and Voyage AI embeddings.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Simplemem.
create_memoryCallable MCP tool function
read_memoryCallable MCP tool function
update_memoryCallable MCP tool function
delete_memoryCallable MCP tool function
search_memoriesCallable MCP tool function
get_backlinksCallable MCP tool function
A vibe-coded memory management system with RAG capabilities for Claude via the Model Context Protocol (MCP).
⚠️ Warning: This project is completely vibe-coded. It works, but don't look too closely at the implementation details. The code was written by an AI having a good time, not by someone following best practices.
SimpleMem is an MCP server that provides persistent memory storage and retrieval for Claude and other MCP clients. It combines traditional file-based storage with modern RAG (Retrieval-Augmented Generation) capabilities, including semantic search and automatic relationship discovery.
Think of it as Claude's personal notebook that never forgets and can find connections between ideas automatically.
Download the latest release for your platform from GitHub Releases:
simplemem-vX.X.X-linux-amd64.tar.gzExtract and place the binary in your PATH.
If you have Nix with flakes enabled:
SimpleMem uses TOML-based configuration with flexible options for API keys and settings.
Create a config.toml file (see config.toml.example for reference):
You can also configure using environment variables:
--config path/to/config.toml--db path/to/database.db (can also be set in config)Add to your MCP client configuration:
create_memory: Create a new memory with metadata object and markdown contentread_memory: Read a specific memory by nameupdate_memory: Update existing memory metadata and contentdelete_memory: Remove a memory and all related datasearch_memories: Semantic search with optional tag filtering (primary discovery method)get_backlinks: Get memories related to a specific memorychange_tag: Modify tags on memoriesNote:
list_memorieshas been temporarily removed to encourage efficient semantic search usage instead of token-heavy full listings.
Memories are stored as YAML frontmatter + Markdown:
For rapid development iteration:
This is a vibe-coded project, so contributions should match the energy:
LGPL 3.0 - Use it, modify it, vibe with it (but share improvements back to the community).
"It works on my machine, and that machine has good vibes." ✨
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