经 AI Skill Hub 精选评估,Mind AI工作流 获评「强烈推荐」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.0 分,适合有一定技术背景的用户使用。
Mind AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
Mind AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:npm 全局安装 npm install -g mind # 方式二:npx 直接运行(无需安装) npx mind --help # 方式三:项目依赖安装 npm install mind # 方式四:从源码运行 git clone https://github.com/GabrielMartinMoran/mind cd mind npm install npm start
# 命令行使用
mind --help
# 基本用法
mind [options] <input>
# Node.js 代码中使用
const mind = require('mind');
const result = await mind.run(options);
console.log(result);
# mind 配置说明 # 查看配置选项 mind --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 MIND_CONFIG="/path/to/config.yml"
Stop losing context across sessions, tools, and time. Give your AI workflow a memory that lasts.
Mind is a local memory layer for AI workflows: a persistent memory system for durable context such as decisions, bug fixes, patterns, checkpoints, and session summaries that would otherwise disappear across sessions and tools.
It supports recovery after compaction through checkpoint and session continuity behavior, while giving humans a way to visualize, inspect, and modify that memory through the CLI and web UI.
Why Mind works above the fold:
- Local persistent store. One SQLite-backed memory system you control. - Built for agent workflows. Use it through the CLI, MCP server, HTTP API, and web UI. - Resumption tools included. Checkpoints and session summaries help recover context and continue work. - Optional file sync. Experimental autosync can mirror project spaces into versioned .mind/ files. - Search when you need it. Full-text search is built in, and semantic search is available as an optional add-on.
Get started with Installation or jump straight to the Quick start.

You can install Mind quickly and start using it right away. If you want agent setup later, jump to Agent setup.
curl -fsSL https://raw.githubusercontent.com/GabrielMartinMoran/mind/main/scripts/install.sh | bash
This installs Mind to user-local paths (no sudo):
~/.local/share/mind~/.local/bin/mindThen run:
mind help
The installer creates a launcher that runs the installed src/mind.ts entry point. It doesn't configure every supported agent automatically. To refresh existing mind-managed agent integrations after installation, run mind setup refresh.
git clone https://github.com/GabrielMartinMoran/mind.git
cd mind
bun install
Mind supports multiple agent integrations, but they are not all equally mature. Run mind setup without an agent name to see the current capability matrix, then configure the specific agent you want.
mind setup # show capability matrix first
mind setup claude-code
mind setup opencode
mind setup cursor
mind setup codex
mind setup windsurf
mind setup gemini-cli
mind setup vscode
mind setup antigravity
mind setup refresh # refresh detected mind-managed integrations
mind setup refresh is conservative by default. It refreshes only detected integrations, where detection means mind finds an existing mind-owned signal, such as an MCP config, managed protocol block, hook/plugin/script, or installed mind-management skill. Use --dry-run to preview changes, --all to refresh all supported agents, or --agent <name> to target one agent.
Most configuration is optional. You only need extra setup if you want to change paths, ports, or enable semantic search.
1. Create your .env file:
cp .env.example .env
Mind ships with a .env.example that contains all configurable options. The installer will also do this automatically if .env doesn't exist.
2. Configure environment variables (optional):
Edit .env to customize your setup:
| Variable | Default | Description |
|---|---|---|
MIND_PORT | 30303 | Port for the web server |
MIND_DATA_DIR | data/ | Directory for SQLite database and data |
MIND_RAG | _(empty)_ | Set to true to enable semantic search |
OPENAI_API_KEY | _(empty)_ | Your OpenAI API key (required for RAG) |
RAG / semantic search setup:
To enable AI-powered semantic search:
```bash
This is the fastest way to see what Mind feels like in practice.
```bash
mind create projects/mind "Mind project memory"
mind add projects/mind architecture "CLI uses command registry + atomic command modules"
mind search architecture
For the full command list:
mind help
MIND_RAG=true OPENAI_API_KEY=sk-your-key-here ```
When enabled, memories are embedded using OpenAI's text-embedding-3-small model and combined with full-text search for hybrid retrieval.
version: 1
Use the commands in Installation to run setup. This section explains how to read the capability matrix and what each integration actually configures.
mind setup (without agent) now prints a capability matrix per integration using a 3-level model:
Each level is explicitly marked as supported, unsupported, or unverified with evidence/fallback notes. If a capability is not implemented, setup output is explicit (no silent skip).
Status labels used here:
supportedunsupported or unverified| **Agent** | **Status** | **Capability reality** |
|---|---|---|
| OpenCode | Complete | L1 supported, L2 supported, L3 supported |
| Claude Code | Complete | L1 supported, L2 supported, L3 supported (opt-in hooks) |
| Codex | Partial | L1 supported, L2 supported, L3 unsupported |
| Cursor | Partial | L1 supported, L2 unverified, L3 supported |
| Windsurf | Partial | L1 supported, L2 unsupported, L3 unsupported |
| Gemini CLI | Partial | L1 supported, L2 unsupported, L3 unsupported |
| VSCode | Partial | L1 supported, L2 unsupported, L3 unsupported |
| Antigravity | Partial | L1 supported, L2 unsupported, L3 unsupported |
Rollout policy:
~/.claude/instructions/mind-memory-protocol.md and maintaining a managed block in ~/.claude/CLAUDE.mdMIND_SETUP_CLAUDE_ENABLE_HOOKS=true before running setup.~/.cursor/hooks.json + managed hook script)~/.gemini/antigravity/mind setup opencode is idempotent and non-destructive:
~/.config/opencode/opencode.jsonc over opencode.json when both exist, and never creates opencode.json if opencode.jsonc is already present. New files are created as opencode.jsonc (the JSONC superset of JSON that OpenCode accepts natively).mcp.mind as local command transport (type: "local", command: ["<path-to-mind>", "mcp"])~/.config/opencode/instructions/mind-memory-protocol.mdinstructions list~/.config/opencode/plugins/mind-automation.js during setupSetup safety contract: all setup flows that touch a user-owned JSON/JSONC config file (opencode, claude fallback, cursor, windsurf, gemini-cli, vscode, antigravity) now go throughsrc/setup/safe-config.ts. Existing files are parsed strictly — a parse failure aborts the run with a clear error rather than overwriting the file with an empty default. Content-changing writes are preceded by a timestamped sibling backup (.bak.YYYYMMDDTHHMMSSmmmZ) and the new content is staged in a sibling.tmpfile and renamed into place so a crash mid-write cannot leave a partial file. The same contract applies tomind setup refresh.
mind setup codex keeps setup idempotent and writes local MCP command args in ~/.codex/config.toml:
[mcp_servers.mind]command = "<path-to-mind>"args = ["mcp"]It also non-destructively upserts a managed Memory Protocol block in ~/.codex/AGENTS.md.
mind setup cursor keeps existing MCP setup behavior and now configures global L3 continuity hooks:
~/.cursor/hooks.json with managed idempotent entries for sessionStart, preCompact, and stop~/.cursor/hooks/mind-session-continuity.shCheck server process status:
mind server-status
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。
AI Skill Hub 点评:Mind AI工作流 的核心功能完整,质量优秀。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | mind |
| 原始描述 | 开源AI工作流:Mind is an automated memory layer for AI workflows. Say goodbye to your agents a。⭐108 · TypeScript |
| Topics | AI工作流TypeScript |
| GitHub | https://github.com/GabrielMartinMoran/mind |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-06-08 · 更新时间:2026-06-08 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端