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Shinobi
Local-first memory layer for AI coding agents
Your AI agent forgets every session. Shinobi gives it persistent memory — decisions, dead-ends, mobile push approvals, multi-machine sync. Local SQLite, no cloud. MIT licensed. MCP server works with Claude Code, Cursor, Cline, Continue.dev, Zed.
Hey PH! Solo dev here.
Shinobi started because I kept re-explaining the same decisions to Claude Code every session. Every conversation began with "remember we picked Postgres, not MongoDB?". The model is brilliant in a single session and a goldfish across sessions.
This is the MCP server I built to fix it. Local-first SQLite, plug into any MCP client (Claude Code, Cursor, Cline, Continue.dev, Zed), your data never leaves your machine unless you opt into the hosted SaaS (coming later).
Install: npm install -g @shinobiapps/shinobi
What's inside:
• Projects + tasks the agent claims/completes across sessions
• Decisions log with rationale (memory across sessions)
• Dead ends — failed approaches the agent doesn't retry
• Notes, voice notes, versioned plans, per-project context
• Web dashboard at localhost:8765 with Cmd+K command palette
• Cross-machine git-based sync, no cloud account required
Happy to answer any questions about the MCP design, the Cloudflare Worker relay for multi-agent sync, or the embedding-provider abstraction (Ollama/Voyage/OpenAI).
About Shinobi on Product Hunt
“Local-first memory layer for AI coding agents”
Shinobi was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #160 on the daily leaderboard. Your AI agent forgets every session. Shinobi gives it persistent memory — decisions, dead-ends, mobile push approvals, multi-machine sync. Local SQLite, no cloud. MIT licensed. MCP server works with Claude Code, Cursor, Cline, Continue.dev, Zed.
On the analytics side, Shinobi competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Shinobi performed against the three products that launched closest to it on the same day.
Who hunted Shinobi?
Shinobi was hunted by shinobi apps. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Shinobi including community comment highlights and product details, visit the product overview.
shinobi apps