Long-term memory for AI assistants. MCP server with hybrid retrieval, query expansion, and automatic topics.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
git clone https://github.com/ambermem/amber{
"mcpServers": {
"amber": {
"command": "node",
"args": ["/path/to/amber/dist/index.js"]
}
}
}Resumen de MCP Servers
# Amber
**Long-term memory for AI assistants.**
Amber is an MCP server that gives any AI assistant persistent, searchable memory across conversations. Your AI remembers preferences, decisions, project context, and personal details - without you doing anything special.
> Just talk normally. Amber stores what matters and finds it when relevant.
## Quick Install
One command. Works with any MCP-compatible client.
### Claude Code / Claude Desktop
```bash
claude mcp add --transport http --scope user amber https://mcp.ambermem.com
```
### Cursor
Add to `~/.cursor/mcp.json` (or `%USERPROFILE%\.cursor\mcp.json` on Windows):
```json
{
"mcpServers": {
"amber": {
"url": "https://mcp.ambermem.com"
}
}
}
```
### ChatGPT
Settings → Connectors → Create → URL: `https://mcp.ambermem.com`
### Windsurf
Add to `~/.codeium/windsurf/mcp_config.json`:
```json
{
"mcpServers": {
"amber": {
"serverUrl": "https://mcp.ambermem.com"
}
}
}
```
### VS Code (GitHub Copilot)
Add to `.vscode/mcp.json`:
```json
{
"servers": {
"amber": {
"type": "http",
"url": "https://mcp.ambermem.com"
}
}
}
```
### Any MCP client
URL: `https://mcp.ambermem.com` | Transport: Streamable HTTP | Auth: OAuth 2.1 (auto-discovered)
## How It Works
1. **You talk to your AI normally.** Amber stores important facts in the background.
2. **Next conversation,** your AI searches Amber automatically when context would help.
3. **Memory improves over time.** The more you use it, the better it gets.
No configuration. No tagging. No manual organization.
## What Makes Amber Different
| Feature | Basic memory servers | Amber |
|---------|---------------------|-------|
| Storage | One embedding per memory | **Multiple semantic variants** per fact |
| Search | Single vector lookup | **Hybrid: vector + keyword + RRF fusion** |
| Queries | Exact match only | **Auto-expanded** (synonyms, paraphrases) |
| Input | Stored as-is | **LLM-chunked** into atomic facts |
| Topics | Manual tags or none | **Auto-categorized** by LLM |
| Time | No temporal awareness | **Natural language time parsing** ("last week", "3 days ago") |
## Technical Details
- **23 MCP tools** (14 memory, 7 account, 2 feedback/notification)
- **Hybrid retrieval pipeline**: vector search + full-text search + Reciprocal Rank Fusion
- **LLM-powered chunking**: text → atomic facts, each independently searchable
- **Multi-variant embeddings**: each fact stored with ~4 paraphrases for higher recall
- **Query expansion**: searches are auto-rephrased to find semantically related memories
- **Automatic topic categorization**: memories grouped by LLM-generated topics
- **Temporal parsing**: "what did I say last week?" just works
- **Async processing**: storage completes in 10-30s background, never blocks your conversation
## Pricing
- **60-day free trial** - no charge, cancel anytime
- **$2.99/month** after trial, via PayPal
- **Cancel instantly** - ask your AI to cancel, or cancel through PayPal directly
- **No lock-in** - export all your data as JSON anytime
## Privacy
- No email collected
- No marketing, no spam
- Data isolated per user (separate database)
- PayPal handles all payment info
- Full export + account deletion available
- GDPR compliant (data minimization by design)
## Architecture
Amber runs on Cloudflare Workers (zero cold starts, global edge deployment) with Turso databases (one per user, full isolation). LLM processing uses Gemini Flash for chunking/expansion and OpenAI for embeddings.
For full technical documentation: [ambermem.com/llms.txt](https://ambermem.com/llms.txt)
## Links
- **Website**: [ambermem.com](https://ambermem.com)
- **MCP endpoint**: `https://mcp.ambermem.com`
- **Privacy policy**: [ambermem.com/privacy](https://ambermem.com/privacy)
- **Terms of service**: [ambermem.com/terms](https://ambermem.com/terms)
- **Technical docs (for AI)**: [ambermem.com/llms.txt](https://ambermem.com/llms.txt)
- **Report a problem**: [ambermem.com/report](https://ambermem.com/report) — no account needed, and it works even when your client cannot connect. In-session, an assistant can also call the `amber_send_feedback_to_developer` tool directly.
## FAQ
**Will it slow my AI down?**
No. Storage is async (background). Search adds <1 second.
**What if Amber shuts down?**
Export all your data as JSON anytime. Your data is always yours.
**Do I need a PayPal account?**
Currently yes. PayPal handles both identity and billing. More login options coming soon.
**Is my data safe?**
Each user gets a completely isolated database. No data is shared between users. Amber has no access to your PayPal payment details.
**Can I self-host?**
Not currently. Amber is a managed service. We handle the infrastructure, scaling, and LLM costs so you don't have to.
Lo que la gente pregunta sobre amber
¿Qué es ambermem/amber?
+
ambermem/amber es mcp servers para el ecosistema de Claude AI. Long-term memory for AI assistants. MCP server with hybrid retrieval, query expansion, and automatic topics. Tiene 1 estrellas en GitHub y su última actualización registrada es del 2026-08-18.
¿Cómo se instala amber?
+
Puedes instalar amber clonando el repositorio (https://github.com/ambermem/amber) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar ambermem/amber?
+
Nuestro agente de seguridad ha analizado ambermem/amber y le ha asignado un Trust Score de 95/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene ambermem/amber?
+
ambermem/amber es mantenido por ambermem. La última actividad registrada en GitHub es del 2026-08-18, con 1 issues abiertos.
¿Hay alternativas a amber?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
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