npx claudepluginhub amanasmuei/amemGive your AI a memory it never forgets. Local-first persistent memory with semantic search, temporal validity, knowledge graph, memory tiers, and privacy controls. 28 MCP tools.
amanasmuei
One memory. Every AI tool.
Tell your AI something once — it remembers across Claude Code, GitHub Copilot, Cursor, Windsurf, and any MCP client.
Local-first · Semantic search · Knowledge graph · Self-evolving · Privacy-aware · No cloud required.
| 72% Recall@5 Semantic accuracy | 0.08ms Search at 10k memories | 29 MCP tools Full memory toolkit | 388 tests All passing |
Quick Start • How It Works • Benchmarks • Tools • Usage Guide • Architecture
Every AI tool starts from zero. Every session. Every tool.
"Don't use
anyin TypeScript" — told Claude three times. Copilot still doesn't know."We chose PostgreSQL over MongoDB" — explained in Cursor. Claude has no idea.
amem gives all your AI tools a shared, persistent memory.
You (in Claude Code): "Don't use any type in TypeScript"
amem stores this as a correction (priority 1.0)
You (switch to Copilot): starts coding
Copilot already knows — amem feeds it the same correction
No cloud. No API keys. Everything stays on your machine.
|
Claude Code (recommended) |
GitHub Copilot CLI |
npm install -g @aman_asmuei/amem
amem-cli init # Detects & configures all installed AI tools
amem-cli rules # Generates extraction rules for proactive memory use
Or configure manually:
{
"mcpServers": {
"amem": {
"command": "npx",
"args": ["-y", "@aman_asmuei/amem"]
}
}
}
Verify it works:
amem-cli stats # Should show "0 memories" initially
Tell your AI: "Remember: always use strict TypeScript, never use any type"
Start a new session: "What do you remember about TypeScript?" — it recalls instantly.
amem captures knowledge in three layers — from fully automatic to fully manual:
| Layer | How | What it does |
|---|---|---|
| Automatic | Lifecycle hooks | Captures tool observations, auto-extracts corrections/decisions/patterns at session end |
| AI-driven | Extraction rules | Your AI proactively calls memory_store when you correct it, make decisions, or express preferences |
| Manual | Natural language | "Remember: we use PostgreSQL" or "Forget the Redis memory" |
| Priority | Type | Example |
|---|---|---|
| 1.0 | correction | "Don't mock the DB in integration tests" |
| 0.85 | decision | "Chose Postgres over Mongo for ACID" |
| 0.7 | pattern | "Prefers early returns over nesting" |
| 0.7 | preference | "Uses pnpm, not npm" |
| 0.5 | topology | "Auth module lives in src/auth/" |
| 0.4 | fact | "API launched January 2025" |
Corrections always surface first — they are your AI's hard constraints.
| Tier | Behavior |
|---|---|
| Core | Always injected at session start (~500 tokens). Your most critical corrections. |
| Working | Session-scoped, auto-surfaced for current task. |
| Archival | Default. Searchable but not auto-injected. |
No description available.
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