LedgerMind
github.com
True zero-touch autonomous memory for AI agents
Description
LedgerMind is a next-generation autonomous memory core for AI agents that achieves genuine zero-touch operation. Using client-side hooks, it automatically: • Searches and injects the most relevant memories before every user prompt • Logs all agent actions including tool calls, file reads, script executions, document analysis and their results • Performs self-healing every 5 minutes • Maintains a full immutable Git-based audit trail • Resolves memory conflicts autonomously It combines hybrid SQLite + vector storage with powerful reasoning capabilities. Currently 100% stable and working out-of-the-box with Gemini CLI. Support for Claude Desktop and Cursor is in active development.
Features
True zero-touch automation via client-side hooks
Automatic memory search + context injection before every prompt
Automatic logging of all agent actions and tool results
Self-healing memory every 5 minutes
Full Git-based immutable audit trail
Autonomous conflict resolution
Use cases
Long-term autonomous AI agents that need reliable persistent memory
Complex multi-step research, coding and data analysis agents
Production-grade agentic workflows requiring consistent context
Agents in Gemini CLI, Claude Desktop and Cursor
Multi-agent systems with shared reliable memory
Specs
| Type | Agent |
| Section | RAG & vector databases |
| Pricing | free |
| Platform | Web + desktop |
| Systems | macos, linux, cli, docker, api, web |
| Site language | en |
| GitHub | sl4m3/ledgermind |
| Rating | 0.00 (0 reviews) |
| Views | 87 |
| Launched | 2026-02-25 |
