No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vbcherepanov · MCP Server · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is total-agent-memory safe to install? View the security audit →
total-agent-memory The only memory layer that learns how you work — not just what you said. Persistent, local memory for AI coding agents: Claude Code, Codex CLI, Cursor, any MCP client. Temporal knowledge graph · procedural memory · AST codebase ingest · cross-project analogy · 3D WebGL visualization. []() []() []() [![Docker GHC
| Stars | 68 |
| Forks | 17 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.4134656787938/100 |
| Last Updated | 2026-09-15 |
| Created | 2026-02-16 |
| Platforms | claude-code, cli, codex, mcp, python |
| Est. Tokens | ~25k |
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total-agent-memory is Persistent local memory for AI coding agents — Claude Code, Codex CLI, Cursor, any MCP client. Temporal knowledge graph, procedural memory, AST codebase ingest, cross-project analogy. LongMemEval R@5 . It is categorized as a MCP Server with 68 GitHub stars.
total-agent-memory is primarily written in Python. It covers topics such as agent-memory, ai-memory, claude-code.
You can find installation instructions and usage details in the total-agent-memory GitHub repository at github.com/vbcherepanov/total-agent-memory. The project has 68 stars and 17 forks, indicating an active community.
total-agent-memory is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to total-agent-memory on Agent Skills Hub include roampal-core, Ori-Mnemos, Zikkaron. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: