Install
$ agentstack add mcp-chrisribe-simple-memory-mcp β scanned Β· β verified β works with Claude Code, Cursor, and more.
Security review
β PassedNo issues found. Passed automated security review. Β· v0.1.0 How review works β
- β Prompt-injection patterns
- β Secret / credential exfiltration
- β Dangerous shell & filesystem operations
- β Untrusted network calls
- β Known-malicious package signatures
What it can access
- β Network access No
- β Filesystem access No
- β Shell / process execution No
- β Environment & secrets No
- β Dynamic code execution No
From automated source analysis of v0.1.0. βUsedβ means the capability is present in the source β more access means more to trust, not that itβs unsafe.
Verified badge
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming β see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps β measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work βAbout
π§ Simple Memory MCP Server
[](https://www.npmjs.com/package/simple-memory-mcp) [](https://opensource.org/licenses/MIT) [](https://www.typescriptlang.org/)
Give your AI assistant persistent memory across sessions.
> ### π Looking for the next evolution? > git-memory is now my daily driver β it builds on the ideas from simple-memory and takes them further. If you're starting fresh, check it out! Simple-memory is still functional but is no longer my main focus.
The problem: AI assistants forget everything when you start a new conversation. Your preferences, project context, decisions - all gone.
The solution: Simple Memory lets AI store and retrieve information that persists forever. Local SQLite database, zero cloud, sub-millisecond fast.
Why not RAG? RAG systems need vector databases, embeddings, chunking strategies, and ongoing maintenance. Simple Memory is just keyword search in SQLite - no ML infrastructure, no API costs, works offline. Perfect for personal knowledge that doesn't need semantic similarity.
How It Works
You: "Remember that I prefer TypeScript over JavaScript and use 4-space indentation"
AI: stores this automatically
...days later, new session...
You: "Help me set up a new project"
AI: searches memory, finds your preferences β Sets up TypeScript with 4-space indentation
The AI handles storage and retrieval automatically. You just chat naturally.
> Simple by design: Keyword search, not semantic. Local SQLite, not cloud. Zero setup, not configuration hell. If you need vector embeddings or team collaboration, see [alternatives](docs/design-philosophy.md#when-to-use-something-else).
π End-to-End Example
Session 1 (January):
You: "I'm using PostgreSQL with TypeScript. Decided on Prisma ORM after
evaluating TypeORM - better type inference and migrations."
AI: β stores automatically with tags [tech-stack, database, decision]
Session 2 (3 weeks later):
You: "Setting up a new microservice, what database setup should I use?"
AI: β searches memories, finds your PostgreSQL + Prisma decision
"Based on your previous work, you standardized on PostgreSQL with Prisma
ORM. You chose it over TypeORM for the better type inference..."
What got stored:
{
"content": "Tech stack decision: PostgreSQL + Prisma ORM. Chose over TypeORM for better type inference and cleaner migrations.",
"tags": ["tech-stack", "database", "decision"],
"relevance": 0.92 // BM25 score when searching "database setup"
}
π€ Why I built this
I got tired of every new conversation starting from zero. I use this daily - saving project status, gotchas, ideas that pop up while Iβm deep in work. Instead of breaking flow to write things down somewhere, I just tell the assistant to save it and keep going. Having it all central means I can reference old solutions, things that failed, things that worked - across projects, across time. Itβs basically an external memory for my dev brain.
β¨ Features
- π§ Persistent Memory - Survives across sessions, restarts, forever
- π Full-Text Search - Find memories by keyword, tags, or content
- π·οΈ Smart Tagging - Organize memories with tags
- πΎ Automatic Backups - Optional sync to OneDrive/Dropbox
- π¦ Zero Config - Works out of the box
- π Fast - Sub-millisecond queries, 2,000-10,000 ops/sec
π Quick Start
Configure MCP Client
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"simple-memory": {
"command": "npx",
"args": ["-y", "simple-memory-mcp"]
}
}
}
VS Code (.vscode/mcp.json):
{
"mcpServers": {
"simple-memory": {
"command": "npx",
"args": ["-y", "simple-memory-mcp"]
}
}
}
Restart your MCP client - that's it! No install needed.
> π‘ Best Experience: Works best with Claude Sonnet in Agent Mode for optimal auto-capture.
Auto-Configure VS Code & Claude Desktop
npx -y simple-memory-mcp setup
This automatically configures all detected installations.
Optional: Install CLI
For command-line usage (search, stats, export/import):
npm install -g simple-memory-mcp
simple-memory setup # auto-configure VS Code & Claude
For Contributors
git clone https://github.com/chrisribe/simple-memory-mcp.git
cd simple-memory-mcp
npm run setup # installs, builds, links, and configures
That's it! The AI assistant can now remember information across conversations.
π» CLI Commands
# Setup - auto-configure VS Code and Claude Desktop
simple-memory setup
# Search memories
simple-memory search --query "typescript" --limit 5
simple-memory search --tags "project,work"
# Store a memory
simple-memory store --content "Remember this" --tags "note"
# Other operations
simple-memory get --hash "abc123..."
simple-memory delete --hash "abc123..."
simple-memory stats
# Export/import
simple-memory export-memory --output backup.json
simple-memory import-memory --input backup.json
Run simple-memory --help for all options.
π οΈ MCP Tools
The AI uses these tools automatically - you don't need to call them directly.
| Tool | Purpose | |------|---------| | memory-graphql | Store, search, update, delete memories | | export-memory | Backup memories to JSON file | | import-memory | Restore memories from JSON file |
GraphQL Schema (for developers)
type Memory { hash, content, title, preview, tags, createdAt, relevance }
type StoreResult { success, hash, error }
type UpdateResult { success, hash, error }
type DeleteResult { success, hash, deletedCount, error }
type Query {
memories(query: String, tags: [String], limit: Int): [Memory!]!
memory(hash: String!): Memory
related(hash: String!, limit: Int): [Memory!]!
stats: Stats!
}
type Mutation {
store(content: String!, tags: [String]): StoreResult!
update(hash: String!, content: String!, tags: [String]): UpdateResult!
delete(hash: String, tag: String): DeleteResult!
}
Note: Mutation results return minimal data (hash/success). To get full memory fields (title, tags, createdAt), query: { memory(hash: "...") { ... } }
βοΈ Configuration
Zero config default: ~/.simple-memory/memory.db
Custom database location:
{
"mcpServers": {
"simple-memory": {
"command": "npx",
"args": ["-y", "simple-memory-mcp"],
"env": {
"MEMORY_DB": "/path/to/memory.db"
}
}
}
}
With automatic backups:
{
"env": {
"MEMORY_BACKUP_PATH": "/path/to/OneDrive/backups",
"MEMORY_BACKUP_INTERVAL": "180"
}
}
π Full configuration guide: [docs/configuration.md](docs/configuration.md)
- Environment variables reference
- Backup strategies
- Cloud storage best practices
- HTTP transport setup
- Multiple database instances
π§ Development
npm install # Install dependencies
npm run build # Build TypeScript
npm test # Run tests
npm run benchmark # Performance benchmarks
Testing:
npm test # GraphQL tests
npm run test:perf # Performance tests
npm run test:migration # Migration tests
π Documentation
| Guide | Description | |-------|-------------| | [Configuration](docs/configuration.md) | Full config reference, backups, cloud storage, HTTP transport | | [Examples](docs/examples.md) | Real-world scenarios, namespace patterns | | [Design Philosophy](docs/design-philosophy.md) | Trade-offs, BM25 relevance scoring | | [Performance](docs/performance.md) | Benchmarks and optimization details | | [Web Server](docs/features/web-server.md) | Visual memory browser interface | | [Changelog](CHANGELOG.md) | Version history |
Developer Docs: [docs/dev/](docs/dev/) - Manual testing, publishing guide, optimization history
π€ Contributing
- Fork the repository
- Create feature branch (
git checkout -b feature/amazing-feature) - Commit changes (
git commit -m 'Add amazing feature') - Push to branch (
git push origin feature/amazing-feature) - Open a Pull Request
π License
MIT License - see [LICENSE](LICENSE) for details.
π Acknowledgments
[β¬ back to top](#-simple-memory-mcp-server)
Made with β€οΈ by chrisribe
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source β we do not rehost the code.
- Author: chrisribe
- Source: chrisribe/simple-memory-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.