ai-memory-vault
Give your AI a real, persistent memory. The open-source system plus templates that turn an Obsidian vault into your AI's working memory. No vector database, just markdown.
No outside reports on file
Only use this with data you wouldn't mind the AI seeing and repeating, keep the vault folder secure on your computer, and regularly review what the AI is storing to catch any problems early.
Based on public adoption and transparency signals as of Oct 27, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesReads local filesNOTED
- Command executionNo shell command runner notedLOW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourceGitHub (jaredrhod/ai-memory-vault)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
No npm or PyPI package is listed. Install from source: github.com/jaredrhod/ai-memory-vault ↗
Everything known
We found nothing about this project in the sources we read (last checked 2026-10-30). That does not mean it has no problems.
0 incidents · 0 advisories · 0 news articles · 0 community threads · checked 2026-10-30
Popularity grade: C (from public signals such as stars and downloads, not a code review). Graded 2026-10-27.
Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-30.
About AI Memory Vault
This skill lets an AI agent store and recall information across conversations using a simple markdown-based filing system (like Obsidian). Instead of using complex databases, it saves notes and memories as regular text files that the AI can read and update, making persistent memory more transparent and portable.
Who it’s for
Developers building AI agents that need to remember context between chats, or people who want to give their AI assistant a "brain" without managing a separate database. It works best if you're comfortable with markdown files and want to see exactly what the AI remembers.
Alternatives
- LangChain memory modules: Built-in options for conversation history and context; well-integrated with AI frameworks. - Supabase with pgvector: A cloud database option with vector search if you want scalable, structured memory. - SQLite with embeddings: Lightweight local database approach; more control than markdown but still simple. - Pinecone or Weaviate: Purpose-built vector databases if you need fast semantic search of memories.
Setup
Check these steps against the project’s own instructions before running anything.
Follow the project's README on GitHub (https://github.com/jaredrhod/ai-memory-vault (opens external site)). The project appears to be an open-source system with templates rather than a standard npm package, so installation steps vary based on which AI platform you're using.
Why this grade
Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 725
- Listing last refreshed
- 2026-10-30
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Risks to watch for
- File system access: The AI gains read/write permission to the vault folder, so it can view and modify all stored notes and memories without restriction. - No built-in access controls: If the vault contains sensitive data (passwords, private notes, financial records), the AI can potentially expose it in responses. - Prompt injection in notes: An attacker could plant hidden instructions inside a note that tricks the AI into misbehaving when it reads that note later. - Unencrypted storage: Memories are stored as plain text files, so anyone with access to your computer can read what the AI remembers. - No data cleanup: Old or sensitive memories don't auto-delete, so stale data can accumulate and be misused.
How to lower the risk
Least-privilege permissions
- Grant the AI read/write access only to the vault folder, not your entire file system.
- Use a separate vault for testing; don't mix production and test memories.
Network isolation
- Keep the vault stored locally; don't sync it to cloud storage unless encrypted.
- Never store API keys or passwords inside vault notes.
Monitoring
- Check the vault folder regularly to see what memories the AI is creating.
- Log which notes the AI reads and writes to spot suspicious patterns.
Red flags to watch for
- Notes appearing that you didn't create or the AI shouldn't remember.
- The AI suddenly behaving differently after accessing a new note.
- Vault folder growing very large or containing unexpected file types.
Questions
How do I install AI Memory Vault?
AI Memory Vault does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/jaredrhod/ai-memory-vault.
Are there security reports about AI Memory Vault?
No reports found for this package in our research (last checked 2026-10-30). AI Memory Vault currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include file system access.
Is AI Memory Vault actively maintained?
AI Memory Vault has 725 GitHub stars. Our directory data was last refreshed on 2026-10-30. Check recent commit activity, release tags, and open issues at github.com/jaredrhod/ai-memory-vault before pinning it in production.
What are alternatives to AI Memory Vault?
Notable alternatives to AI Memory Vault include LangChain memory modules (Built-in options for conversation history and context). You can also compare AI Memory Vault side by side with other skills in the Related tools section on this page.
README badge and team notes
Maintain or use AI Memory Vault? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.
GitHub README Markdown:
[](https://agentarmorhq.com/skills/jaredrhod-ai-memory-vault)HTML embed:
<a href="https://agentarmorhq.com/skills/jaredrhod-ai-memory-vault"><img src="https://agentarmorhq.com/api/badge/jaredrhod-ai-memory-vault" alt="AgentArmorHQ Risk Grade for AI Memory Vault" height="20" /></a>Terminal check:
curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "jaredrhod-ai-memory-vault"Share with your security lead
Need sign-off to use ai-memory-vault? Copy this note for Slack, a ticket or a pull request.
### AgentArmorHQ Security Review Memo: ai-memory-vault
- **Listing URL:** https://agentarmorhq.com/skills/jaredrhod-ai-memory-vault
- **Type:** AI agent skill
- **Risk Grade:** Grade C (Moderate risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 725 GitHub stars
#### Permission & Blast-Radius Signals
- **Local files:** Reads local files
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** GitHub (jaredrhod/ai-memory-vault)
#### Recommended Hardened Setup
- **Source Repo:** https://github.com/jaredrhod/ai-memory-vault
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.
_Based on public adoption and transparency signals as of Oct 27, 2026. Our opinion, not a code audit or security guarantee._Key facts
- Type
- AI agent skill
- Publisher
- jaredrhod
- Source code
- github.com/jaredrhod/ai-memory-vault
- Est. context load
- ~71 tokens idle · ~450 tokens when active (on-demand skill)
- Popularity
- 725 GitHub stars
- Last updated
- 2026-10-30
- Last graded
- 2026-10-27
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