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Local-first memory lifecycle for AI agents
A Rust-based memory layer for AI agents that stores, recalls, and consolidates memory locally with SQLite/FTS. It is built for developers who want explainable recall, explicit forgetting, and portable agent memory without a required cloud service.
Agenticness = how independently a tool can take action, scored across 9 dimensions. Scored independently by David Kooi, Skylark Creations — see full rubric →
File Access
Memory
B2B
CLI
Self-Hosted
On-Device / Edge
Model Agnostic
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About
What It Is
What to Know
Key Features
Rust-native CLI and crates
Local SQLite/FTS storage
Explainable recall with ring, scope, confidence, and ranking signals
Explicit forgetting, redaction, supersession, and expiry
Deterministic consolidation without requiring an LLM
Use Cases
Adding persistent memory to a custom AI agent stack
Storing and recalling project-scoped lessons for development workflows
Keeping durable decisions, warnings, and preferences separate from raw transcripts
Agenticness
: Guided Assistant
Executes tasks you assign, one step at a time, within narrow domains.
High evidence
Last evaluated:
Jul 31, 2026
Dimension Breakdown
Action Capability
Autonomy
Planning
Adaptation
State & Memory
Reliability
Interoperability
Safety
Operator Sovereignty
Categories
Pricing
- Free / open source — full functionality available at no cost.
Details
AddedJuly 16, 2026
RefreshedJuly 16, 2026
Agenticness
Quick Facts
DeploymentSelf-hosted
AutonomyCopilot (human-in-loop)
Model supportMulti-model
Team supportIndividual only
Pricing modelFree / open source
Interfacecli
Sources
Last updated
August 18, 2026
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