
Mem
- 2.4k installs
- 6 repo stars
- Updated March 21, 2026
- runablehq/memory
mem is a CLI skill for storing and retrieving agent memories in local SQLite with tags, search, and image attachments.
About
The mem skill documents a CLI agent memory store backed by a local SQLite database at ~/.mem/mem.db with full-text search across notes, facts, decisions, and code snippets. Three operators define the workflow: no flag recalls or searches, plus remembers new content, and minus forgets by ID. Recall supports query strings, tag filters, limit and JSON output, and lookup by memory ID. Remember accepts inline text, piped content, tags, and image attachments with titles. Best practices emphasize consistent lowercase tags, searching before asking the user again, storing architectural decisions with reasoning, and keeping each memory atomic for better retrieval. Output modes include one-line summaries, full inline content, and structured JSON for scripting. Piping examples show bulk delete via jq and xargs. Agents invoke mem when they need durable cross-session recall of preferences, commands, configurations, or screenshots without a hosted memory service.
- Local SQLite store at ~/.mem/mem.db with full-text search.
- Three operators: recall (default), remember (+), forget (-).
- Tag filtering, JSON output, and image attachment support.
- Search before asking users for information already stored.
- Atomic memories with consistent lowercase tags improve retrieval.
Mem by the numbers
- 2,356 all-time installs (skills.sh)
- +4 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #405 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 4, 2026 (Skillselion catalog sync)
mem capabilities & compatibility
- Capabilities
- full text recall and tag filtered search · remember text, piped content, and images with ta · forget by single or multiple memory ids · json and full content output modes · best practice guidance for atomic tagged memorie
- Use cases
- memory · planning
- Runs
- Runs locally
- Pricing
- Free
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| Installs | 2.4k |
|---|---|
| repo stars | ★ 6 |
| Security audit | 3 / 3 scanners passed |
| Last updated | March 21, 2026 |
| Repository | runablehq/memory ↗ |
How does an agent remember user preferences, decisions, and snippets across sessions without re-asking?
Store and retrieve agent memories in a local SQLite database with full-text search, tags, and optional image attachments via the mem CLI.
Who is it for?
Agents needing lightweight local memory with tags, search, and optional screenshot storage.
Skip if: Skip for team-shared cloud memory, vector semantic search, or multi-user knowledge bases.
When should I use this skill?
User asks to remember a fact, recall prior decisions, search stored notes, or attach a screenshot to memory.
What you get
Tagged memories stored locally and retrieved via full-text search or ID lookup before responding.
- searchable memory database
- stored snippets and decisions
- retrieved context for agent prompts
By the numbers
- Stores data locally in ~/.mem/mem.db SQLite with full-text search
Files
mem — Agent Memory Store
A CLI tool for storing and retrieving memories with full-text search. Data is stored locally in ~/.mem/mem.db.
When to Use
- Remember user preferences, project decisions, important facts
- Store code snippets, commands, configurations for later recall
- Search your knowledge base before asking the user for information you may have stored
- Attach images (screenshots, diagrams) to memories
Commands
Three operators: (none) = recall, + = remember, - = forget.
Recall (search, list, get)
mem # list recent memories
mem "deploy" # full-text search
mem "database" --tag db # search filtered by tag
mem 7sjtNVyZrNIa # get full content by ID
mem --tag prefs # list filtered by tag
mem "api" --limit 5 --json # limit results, JSON output
mem --full # show full content for allRemember
mem + "user prefers dark mode" --tag prefs
mem + "deploy: bun build --compile" --tag deploy
mem + "chose SQLite for simplicity" --tag architecture
mem + --image ./screenshot.png --title "Current UI" --tag ui
echo "long content" | mem + --tag notesForget
mem - <id> # delete one memory
mem - id1 id2 id3 # delete multiplePiping
mem "old" --json | jq -r '.[].id' | xargs -I{} mem - {}
echo "long content" | mem + --tag notesBest Practices
1. Tag consistently — Use lowercase, descriptive tags like prefs, api, deploy, db 2. Search before asking — Check if you've stored relevant information before asking the user 3. Store decisions — When making architectural or design decisions, store the reasoning 4. Keep memories atomic — One concept per memory for better searchability
Output Formats
- Default: One-line summary per result
--full: Complete content inline--json: Structured JSON for parsing
Related skills
How it compares
Choose mem when you want a local SQLite-backed agent memory CLI instead of cloud-hosted or vendor-locked session context.
FAQ
Where is data stored?
Locally in ~/.mem/mem.db as SQLite with full-text search; no cloud sync is documented.
How do I delete memories?
Use mem - <id> for one ID or pass multiple IDs; pipe jq output from --json for bulk delete.
Should I search before asking the user?
Yes. The skill recommends checking stored memories before requesting information the agent may already have.
Is Mem safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.