MCP Catalogs
Home

superlocalmemory

by qualixar·150·Score 50

A local-only AI memory system with MCP integration for unlimited memory across AI clients.

ai-llmdeveloper-toolsproductivity
18
Forks
10
Open issues
this month
Last commit
2d ago
Indexed

Overview

SuperLocalMemory is a privacy-focused AI memory system that operates entirely on your device, sending no data to external APIs or cloud services. It implements advanced mathematical techniques from differential geometry, algebraic topology, and stochastic analysis to provide memory retrieval without requiring external LLM calls. The system offers multiple modes: Mode A (local-only, zero-LLM), Mode B (with optional cloud), and Mode C (with local LLM). It provides dual interfaces as both an MCP server and a CLI tool, with extensive documentation and IDE integrations.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Enhancing AI coding assistants like Claude Code, Cursor, and Windsurf with persistent memory across sessions
you:Building private, on-device AI agents with unlimited memory that never send data to cloud services
you:Creating research applications requiring GDPR/EU AI Act compliance with no external data transmission
you:How does SuperLocalMemory work without cloud LLMs?
you:Which AI clients support SuperLocalMemory?

When to choose this

Choose SuperLocalMemory when you need persistent memory for AI agents with strict privacy requirements and cannot use cloud services. Ideal for developers working with sensitive code or requiring offline functionality.

When NOT to choose this

Not recommended if you need cloud-based memory sharing across multiple devices, or if you prefer cloud-hosted solutions with simpler setup. The AGPL-3.0 license may also be restrictive for some commercial use cases.

Tools this server exposes

12 tools extracted from the README
  • forget

    Programmatic memory archival via lifecycle rules

  • quantize

    Trigger smart compression on demand

  • consolidate_cognitive

    Extract and store patterns from memory clusters

  • get_soft_prompts

    Retrieve auto-learned patterns for context injection

  • reap_processes

    Clean orphaned SLM processes

  • get_retention_stats

    Memory lifecycle analytics

  • remember

    Store new information in memory

  • recall

    Retrieve information from memory

  • status

    Check memory system status

  • warmup

    Pre-download embedding models

  • migrate

    Migrate memory data between versions

  • doctor

    Verify memory system is working correctly

Comparable tools

mem0lettazepgraphiti

Installation

Install via npm (recommended)

npm install -g superlocalmemory
slm setup     # Choose mode (A/B/C)
slm doctor    # Verify everything is working
slm warmup    # Pre-download embedding model (~500MB, optional)

Install via pip

pip install superlocalmemory

MCP Integration (Claude, Cursor, Windsurf, VS Code, etc.)

{
  "mcpServers": {
    "superlocalmemory": {
      "command": "slm",
      "args": ["mcp"]
    }
  }
}

FAQ

How does SuperLocalMemory work without cloud LLMs?
It uses advanced mathematical techniques from differential geometry, algebraic topology, and stochastic analysis to replace the work typically done by LLMs for similarity scoring, contradiction detection, and lifecycle management.
Which AI clients support SuperLocalMemory?
It works with any MCP-compatible client including Claude Code, Cursor, Windsurf, VS Code Copilot, Continue, Cody, ChatGPT Desktop, Gemini CLI, JetBrains, Zed, and Antigravity.

Compare superlocalmemory with

GitHub →

Last updated · Auto-generated from public README + GitHub signals.