agent-memory-vault — Claude Skill by mcncarl

by mcncarl · Claude Skill · ★ 145

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About agent-memory-vault

Agent Memory Vault: Shared Claude Code + Codex 这是一个可由 Claude Code 与 Codex 共用的长期记忆库模板。它把普通 Markdown 文件当作唯一长期事实源,用 SQLite 建全库索引,并用少量固定字段支持按用户、Agent、项目、应用、会话和记忆类型过滤。需要语义检索时,也可以额外启用本地 EmbeddingGemma + Zvec 向量旁路。 这个仓库只包含模板、脚本和假示例,不应该包含你的真实记忆、真实路径、API key、私人项目名或聊天原文。 所有运行入口都使用平台中立命名:配置使用 ,脚本使用 ,统一命令为 。仓库不提供旧名称兼容脚本或环境变量回退。 它解决什么问题 让 Claude Code 与 Codex 每次开始重要任务时,读取同一份相关长期记忆。 让每次任务结束时,把稳定事实、项目状态、工作流和 Agent 经验沉淀到 Markdown。 让 Markdown 仍然是源文件,SQLite 只做索引和搜索,Obsidian 只是可选的查看和编辑方式。 可选增加向量检索:只记得大概意思时,用 embedding + Zvec 找到相关 Markdown,再回读原文。 把真实信息留在本地私有 vault,模板只提供结构和方法。 是否必须安装 Obsidian? 不必须。 这个项目本质上是一个 Markdown 文件夹 + SQLite 索引脚本。你可以直接用 Codex、VS Code 或任意文本编辑器管理它。 如果你想用更舒服的笔记界面查看、编辑和搜索这些 Markdown 文件,可以安装 Obsidian,然后把生成出来的记忆库文件夹作为一个 Obsidian vault 打开。 核心结构 text templates/vault/ AGENTS.md # 两端共享的读取和写入规则 INDEX.md # 记忆路由索引 用户记忆/ # 用户偏好、边界、长期画像 项目/ # 项目级状态和结论 工作流/ # 可复用流程、字段规范、收尾规则 决策/ # 权衡和取舍 agent/ # Agent case、skill 候选、未闭环事项 scripts/ bootstrap.py # 从模板创建本地私有 vault agentmemoryindex.py # 全库 SQLite 索引和搜索 agentmemorysearch.py # 统一搜索入口:SQLite + 可选 Zvec + 手动 rg agentmemoryclaim.py # 会话文件认领账本,防止 Claude/Codex 串提交 agentmemorycloseout.py # 任务结束收尾:检查、对账、刷新索引、审计、可选提交 agentmemoryaudit.py #...

agent-memoryclaude-codecodexobsidiansqlitevector-search

Quick Facts

Stars145
Forks15
LanguagePython
CategoryClaude Skill
LicenseMIT
Quality Score68.8383507233058/100
Open Issues3
Last Updated2026-07-12
Created2026-06-20
Platformsclaude-code, codex, python
Est. Tokens~15k

Compatible Skills

These tools work well together with agent-memory-vault for enhanced workflows:

  • ogham-mcp — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)
  • rekal — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (62%)
  • iai-personal-memory-engine — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (62%)

agent-memory-vault alternative? Top 6 similar tools

Looking for a agent-memory-vault alternative? If you're comparing agent-memory-vault with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • memorix by AVIDS2 · ⭐ 580

    Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Wi

  • Ori-Mnemos by aayoawoyemi · ⭐ 314

    Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.

  • signetai by Signet-AI · ⭐ 220

    Local-first identity, memory, and secrets for AI agents. Portable state across models and harnesses.

  • obsidian-plugin-skill by gapmiss · ⭐ 174

    Agent SKILL for Obsidian.md plugin development

  • Overture by SixHq · ⭐ 592

    Overture is an open-source, locally running web interface delivered as an MCP (Model Context Protocol) server

  • codex-mcp-server by tuannvm · ⭐ 467

    MCP server wrapper for OpenAI Codex CLI that enables Claude Code to leverage Codex's AI capabilities directly.

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Frequently Asked Questions

What is agent-memory-vault?

agent-memory-vault is Markdown-first shared memory vault for Claude Code and Codex with SQLite, Zvec, Git, closeout, and audit. It is categorized as a Claude Skill with 145 GitHub stars.

What programming language is agent-memory-vault written in?

agent-memory-vault is primarily written in Python. It covers topics such as agent-memory, claude-code, codex.

How do I install or use agent-memory-vault?

You can find installation instructions and usage details in the agent-memory-vault GitHub repository at github.com/mcncarl/agent-memory-vault. The project has 145 stars and 15 forks, indicating an active community.

What license does agent-memory-vault use?

agent-memory-vault is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to agent-memory-vault?

The top alternatives to agent-memory-vault on Agent Skills Hub include memorix, Ori-Mnemos, signetai. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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