AI agent memory with mathematical foundations. Store, recall, search, and manage memories locally. Local data root; optional networked features have separate behavior.
232 stars
0 votes
0 copies
0 views
Added October 13, 2026
ai-agentsgobashgitapici/cd
Works with
claude code
cursor
cli
api
mcp
Security analysis
A92/100
mediumInstalls packages at runtime which could introduce malicious dependencies
mediumInstalls packages at runtime which could introduce malicious dependencies
Installs into .claude/skills of the current project.
Are you the author of superlocalmemory?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/qualixar-superlocalmemory)
---
name: superlocalmemory
description: "AI agent memory with mathematical foundations. Store, recall, search, and manage memories locally. Local data root; optional networked features have separate behavior."
version: "4.1.25"
author: "Varun Pratap Bhardwaj"
license: AGPL-3.0-or-later
homepage: https://superlocalmemory.com
repository: https://github.com/qualixar/superlocalmemory
triggers:
- remember something
- recall memory
- search memories
- memory status
- store fact
- agent memory
- local memory
- memory health
- save a picture
- save a PDF
- message another bot
---
# 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
```bash
pip install superlocalmemory
# or
npm install -g superlocalmemory
```
## Quick Start
```bash
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
```bash
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
```
### Pictures, documents and folders (4.1.25, optional)
Off by default. Needs a computer with 16 GB of memory and downloads about 1.5 GB.
Ask the user before turning it on.
```bash
slm media status --json # is it on, and how is set-up going
slm media enable # asks first; --yes skips the question (only with the user's yes)
slm media disable # memories are kept
slm media repair --dry-run # count pictures that cannot be found by what they show yet
slm sources add ~/Notes --kind obsidian # or --kind folder; read-only; shows what would be read, then asks
slm sources list --json
```
When it is on, a normal `slm recall` also returns saved pictures and PDF pages (a
`media` block per result). The MCP tools are `remember_media`, `remember_document`,
`get_media`, `media_status` and, for web apps, `media_upload_link`; they are listed
only in the `full`, `power` and `whole` tool sets. A picture is up to 25 MB, a PDF up
to 100 MB and 500 pages. Do not save a file that shows a secret. The `slm-media` skill
has the details.
### Company mode and the dashboard key
```bash
slm team status --json # Require login: on|off, user count
slm team policy --require-login on|off # on the SLM computer; only when the user asks
slm token show # the key the dashboard asks for in strict mode; a secret, never paste it into chat
```
### Diagnostics
```bash
slm status --json # System status (mode, profile, DB)
slm health --json # Math layer health
slm trace "<query>" --json # Recall with per-channel breakdown
```
### Configuration
```bash
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
```bash
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)
```bash
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:
```json
{
"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:
```json
{
"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 -- a model on this machine (Ollama by default, any local server works), data stays on your machine | Local only |
| C | Full Power -- your own endpoint, or a cloud provider, for maximum accuracy | Yes, unless using a keyless custom endpoint |
## Dual Interface
SuperLocalMemory works via both MCP and CLI:
- **MCP**: 38 tools (`code` profile), 57 (`full`, the default; 62 with pictures and documents on) for IDE integration (Claude Code, Cursor, Windsurf, VS Code, JetBrains, Zed); includes bounded-loop tools `slm_loop_run/history/show`, bot-message tools `mesh_peers`, `mesh_send`, `mesh_inbox`, `mesh_wait` (a connected web app passes each reply's `ack_ids` back as `ack`) and `mesh_state`
- **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)