Local-first AI memory with knowledge graphs and hybrid search. 17+ AI tools via MCP. Free.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"superlocalmemory": {
"args": [
"mcp"
],
"command": "slm"
}
}
}Are you the author?
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Every major AI memory system — Mem0, Zep, Letta, EverMemOS — sends your data to cloud LLMs for core operations. That means latency on every query, cost on every interaction, and after August 2, 2026, a compliance problem under the EU AI Act.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y 'superlocalmemory' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked superlocalmemory against OSV.dev.
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Cache. Compress. Remember. Three surfaces — proxy, MCP tools, or skill. Every setup covered.
To the best of our knowledge, the only zero-cloud agent memory that beats Mem0's zero-LLM score on LoCoMo. Mode A: 74.8% vs Mem0 64.2% — no GPU, no API key, on CPU.
v3.6.18 — Plugin-native. Profile-aware. Distributed-ready.
Proxy: slm wrap claude · MCP: add slm_compress to your config · Skill: zero-config
3 published research papers (arXiv preprints + Zenodo-archived) · arXiv:2603.02240 · arXiv:2603.14588 · arXiv:2604.04514
Every hosted AI memory platform — Mem0 Cloud, Zep Cloud, Letta Cloud, EverMemOS Cloud — sends your data to cloud LLMs by default. Self-hosted variants exist but require Docker, a separate graph DB, or Ollama config, and most default to OpenAI until you flip env vars. After August 2, 2026, any of those cloud paths becomes a compliance question under the EU AI Act.
SuperLocalMemory V3 uses mathematics instead of cloud compute — differential geometry, algebraic topology, and stochastic analysis replace the work other systems need LLMs to do. Local-first out of the box. No Docker. No graph DB. No API keys. CPU-only.
Benchmark results (evaluated on LoCoMo, the standard long-conversation memory benchmark, published April 2026):
| System | Score | Config | Cloud LLM required? | Open Source | Source |
|---|---|---|---|---|---|
| EverMemOS | 93.05% | Cloud (proprietary) | Yes | Core only | evermind.ai (Feb 2026) |
| Hindsight (LoComo10) | 92.0% | Cloud | Yes | No | benchmarks.hindsight.vectorize.io (Apr 2026) |
| Mem0 (token-efficient) | 91.6% | Hybrid (Cohere/Open |