io.github.jagoff/memo

MCPcommunity
v0.8.0io.github.jagoffUnknownUpdated 1mo agoGitHub

Local MLX-native memory for AI agents — markdown-on-disk, sqlite-vec + BM25 hybrid, zero cloud.

Persistent semantic memory for AI agents — 100% local, MLX-native, Apple Silicon. gives any MCP-aware agent (Claude Code, Claude Desktop, Cursor, Cline, Continue, …) a long-term memory that runs entirely on your Mac. It stores each memory as a plain Markdown file inside an Obsidian-friendly folder, indexes embeddings in a single sqlite file, and runs the LLM + embedder + reranker in-process via…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
1mo agoLast update
Package
Authorio.github.jagoff
LicenseUnknown
Version0.8.0
Sourcemcp-registry
GitHubjagoff/memo
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/25
→ Publisher: run `forge publish` from the package repo to claim ownership
—Ed25519 publish signature+0/10
→ Included automatically when the publisher runs `forge publish`
—Domain verification+0/5
→ Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
✓CVE scan · clean+30/30
✓Static analysis · clean+20/20
—npm provenance (Sigstore)+0/5
→ Publish from GitHub Actions with the --provenance flag
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance—
DependenciesNot audited
Tool surface—
Security scan✓ Cleanv0.8.0 · 19d ago
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

Persistent semantic memory for AI agents — 100% local, MLX-native, Apple Silicon. gives any MCP-aware agent (Claude Code, Claude Desktop, Cursor, Cline, Continue, …) a long-term memory that runs entirely on your Mac. It stores each memory as a plain Markdown file inside an Obsidian-friendly folder, indexes embeddings in a single sqlite file, and runs the LLM + embedder + reranker in-process via Apple MLX — no Ollama, no Qdrant, no cloud API, no keys. Your prompts and memorias never leave the…

Keywords
mcp