memX智能记忆系统 是 AI Skill Hub 本期精选AI工具之一。综合评分 7.8 分，整体质量较高。我们推荐使用将其纳入你的 AI 工具库，帮助提升工作效率。
memX智能记忆系统 是一款基于 TypeScript 开发的开源工具，专注于 智能体记忆、自学习框架、工作流引擎 等核心功能。作为 GitHub 开源项目，它拥有活跃的社区支持和持续的版本迭代，代码完全透明可审计，支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流，都能提供稳定可靠的解决方案。
memX智能记忆系统 是一款基于 TypeScript 开发的开源工具，专注于 智能体记忆、自学习框架、工作流引擎 等核心功能。作为 GitHub 开源项目，它拥有活跃的社区支持和持续的版本迭代，代码完全透明可审计，支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流，都能提供稳定可靠的解决方案。
# 方式一：npm 全局安装 npm install -g memx # 方式二：npx 直接运行（无需安装） npx memx --help # 方式三：项目依赖安装 npm install memx # 方式四：从源码运行 git clone https://github.com/NeoLi00/memX cd memX npm install npm start
# 命令行使用
memx --help
# 基本用法
memx [options] <input>
# Node.js 代码中使用
const memx = require('memx');
const result = await memx.run(options);
console.log(result);
# memx 配置说明 # 查看配置选项 memx --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量（覆盖配置文件） export MEMX_CONFIG="/path/to/config.yml"
<p align="center"> <img src="./assets/memx-cover-en.svg" alt="memX - self-learning, self-maintaining memory for AI agents" width="920"> </p>
<p align="center"> <a href="./README.md">English</a> · <a href="./README-ch.md">中文</a> · <a href="./ARCHITECTURE.md">Architecture</a> </p>
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memX turns completed work into structured, searchable, self-maintained memory, then injects only the evidence an agent needs for the current query. It connects natively to Codex, Claude Code, and OpenClaw, and reaches any MCP-compatible client through the same local memory layer.
Each uninstall command backs up the target config first, then removes only memX-owned entries. Claude Code and Codex cleanup also uninstall the native plugin, remove the local marketplace, and delete the generated marketplace snapshot. OpenClaw cleanup also removes stale memx / memory-memx slot, allow, and entry references, then best-effort uninstalls both current and legacy plugin files if OpenClaw can still see them.
npx -y -p github:NeoLi00/memX memx uninstall openclaw
npx -y -p github:NeoLi00/memX memx uninstall codex
npx -y -p github:NeoLi00/memX memx uninstall claude-codeAdd --dry-run to preview, or --config /path/to/config when using a non-default config path.
Requirements: Node.js 22.14+ or Node 24. OpenClaw installs require OpenClaw 2026.3.25+. Python 3 is needed only for the default local embedding runtime.
The README commands use the GitHub package spec. A fresh run pulls current GitHub code, so installs do not wait for an npm publish. To use the npm release channel later, replace github:NeoLi00/memX with @neoli00/memx.
Fill in these values before running a command:
- --llm-provider: the provider adapter memX should call. Choose one of openai-compatible, anthropic, google, or ollama. - --llm-base-url: the base URL for that provider. Examples: https://api.openai.com/v1, https://api.anthropic.com/v1, https://generativelanguage.googleapis.com/v1beta, or http://127.0.0.1:11434 for Ollama. - --llm-model: the model memX uses for memory compilation, recall planning, and maintenance. Pick a fast, low-cost model with reliable JSON output. - --llm-api-key: the API key for the provider. Use --llm-api-key-env PROVIDER_API_KEY if you want the config to reference an environment variable instead of storing plaintext. For local Ollama, omit the key.
The default embedding setup is local sentence-transformers-local with intfloat/multilingual-e5-small. Add --embedding-provider and --embedding-model only when you want to override that default. Use --dry-run to preview the files and exec-form commands before writing anything.
For Codex and Claude Code, native hooks are the default lifecycle path for automatic recall and turn capture. Their MCP server uses --mcp-tools none by default, so no memX tools are exposed to the agent; this prevents duplicate recall/write and prevents the agent from reading audit data as a side channel. Use --mcp-tools full only when you intentionally want the agent to see the complete MCP tool set. Generic MCP quickstart stays full by default because it has no native lifecycle hooks. Default native memories are also host-scoped, so Codex and Claude Code do not share the same local database unless you deliberately override the database path and actor settings.
创新性内存管理方案，为AI智能体赋予持久学习能力。TypeScript生态完整，架构清晰。项目新颖但成熟度待观察，适合前沿AI开发者。
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
经综合评估，memX智能记忆系统 在AI工具赛道中表现稳健，质量良好。如果你已有明确的使用需求，可以直接上手体验；如果还在评估阶段，建议对比同类工具后再做决策。
| 原始名称 | memX |
| 原始描述 | 开源AI工作流：memX: self-learning, self-maintaining memory for AI agents; native support for c。⭐81 · TypeScript |
| Topics | 智能体记忆自学习框架工作流引擎向量存储Claude集成 |
| GitHub | https://github.com/NeoLi00/memX |
| License | MIT |
| 语言 | TypeScript |
收录时间：2026-05-21 · 更新时间：2026-05-22 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。