AGPL-3.0-or-laterBackend Notes

SuperLocalMemory

Name: SuperLocalMemory
Author: qualixar

By qualixar· qualixar/superlocalmemory· 0

Store and search AI agent memories locally with mathematical ranking and entity graph scoring.

Installation

1
Make sure Claude is on your device and in your terminal.
Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.
One-time setup
```
npm i -g @anthropic-ai/claude-code
```
Already have it? Skip ahead.

Paste into Claude Code or into your terminal.

Install

git clone ht•••••••••••••••••••••••••••••••••••••••••••••• ••••••••••••••••••••••••••••••• •• ••••• •• •••••••••••••••••••••••••••••••••••••••••• •• •• •• ••••••••••••••••••••••••••••••••••• •••••••••••••••••••••••••••••••••••••••••••

This copies the whole skill folder into ~/.claude/skills/superlocalmemory-qualixar/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

Faster alternative (instruction-only skills)

Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

Quick install (SKILL.md only)

mkdir -p ~/.••••••••••••••••••••••••••••••••••••••• •• •••• ••••• ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• •• •••••••••••••••••••••••••••••••••••••••••••••••••••

Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.
Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

AI agent memory with mathematical foundations. Store, recall, search, and manage memories locally. Local data root; optional networked features have separate behavior.

What this skill does

SuperLocalMemory

AI agent memory with a local data root. Five candidate producers (semantic, BM25, temporal, spreading-activation, Hopfield) fuse via RRF, with an entity-graph post-fusion score enhancement — all with mathematical similarity scoring. Mode A operates without sending memory content to a cloud model provider; optional connectors, backup, and proxy providers are explicit choices with separate behavior.

Installation

pip install superlocalmemory
# or
npm install -g superlocalmemory

Quick Start

slm remember "Alice works at Google as a Staff Engineer" --json
slm recall "Who is Alice?" --json
slm status --json

Commands

All data-returning commands support --json for structured agent-native output.

Memory Operations

slm remember "<content>" --json           # Store a memory
slm remember "<content>" --tags "a,b" --json
slm recall "<query>" --json               # Semantic search
slm recall "<query>" --limit 5 --json
slm list --json -n 20                     # List recent memories
slm forget "<query>" --json               # Preview matches (add --yes to delete)
slm forget "<query>" --json --yes         # Delete matching memories
slm delete <fact_id> --json --yes         # Delete specific memory by ID
slm update <fact_id> "<content>" --json   # Update a memory

Diagnostics

slm status --json                         # System status (mode, profile, DB)
slm health --json                         # Math layer health
slm trace "<query>" --json                # Recall with per-channel breakdown

Configuration

slm mode --json                           # Get current mode
slm mode a --json                         # Set mode (a=local, b=ollama, c=cloud)
slm profile list --json                   # List profiles
slm profile switch <name> --json          # Switch profile
slm profile create <name> --json          # Create profile
slm connect --json                        # Auto-configure IDEs
slm connect --list --json                 # List supported IDEs

Bounded Loops

slm loop demo                             # Run built-in convergence demo (no API key needed)
slm loop history [--name <loop-name>]     # List recorded runs from SLM memory
slm loop show <run_id>                    # Show every lap of one run

Loop laps are persisted to SLM memory under the tag loop:<name>. MCP tools slm_loop_run, slm_loop_history, and slm_loop_show are available in the code and full profiles.

Services (no --json)

slm setup                                 # Interactive setup wizard
slm mcp                                   # Start MCP server (for IDE integration)
slm dashboard                             # Open web dashboard
slm warmup                                # Pre-download embedding model

JSON Envelope

Every --json response follows a consistent envelope:

{
  "success": true,
  "command": "recall",
  "version": "4.0.0",
  "data": {
    "results": [
      {"fact_id": "abc123", "score": 0.87, "content": "Alice works at Google"}
    ],
    "count": 1,
    "query_type": "semantic"
  },
  "next_actions": [
    {"command": "slm list --json", "description": "List recent memories"}
  ]
}

Error responses:

{
  "success": false,
  "command": "recall",
  "version": "4.0.0",
  "error": {"code": "ENGINE_ERROR", "message": "Description of what went wrong"}
}

Operating Modes

Mode	Description	Cloud Required
A	Local Guardian -- core memory runs without a cloud model provider; optional connectors and model downloads may use the network	None (for core memory)
B	Smart Local -- local Ollama LLM, data stays on your machine	Local only
C	Full Power -- cloud LLM for maximum accuracy	Yes

Dual Interface

SuperLocalMemory works via both MCP and CLI:

MCP: 24 tools (code profile) for IDE integration (Claude Code, Cursor, Windsurf, VS Code, JetBrains, Zed); includes bounded-loop tools slm_loop_run/history/show
CLI: commands with --json for scripts, CI/CD, and agent frameworks; includes slm loop demo/history/show

Part of Qualixar | Author: Varun Pratap Bhardwaj (qualixar.com | varunpratap.com)

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