MineEcho
MineEcho 是 AI Skill Hub 本期精选Agent工作流之一。综合评分 7.5 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。
📚 深度解析
MineEcho 工作流的设计遵循"最小配置，最大复用"原则：核心逻辑已经封装好，用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制，在网络波动或 API 限速等情况下仍能稳定运行，适合作为生产环境的自动化基础设施。
在实际部署时，建议先在测试环境中运行 3-5 次，验证各个环节的输出结果符合预期，再部署到生产环境。AI Skill Hub 评分 7.5 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
MineEcho 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。
📖 中文文档
MineEcho 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。
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
# 方式一：npm 全局安装 npm install -g mineecho # 方式二：npx 直接运行（无需安装） npx mineecho --help # 方式三：项目依赖安装 npm install mineecho # 方式四：从源码运行 git clone https://github.com/Health-Yang/MineEcho cd MineEcho npm install npm start
- 访问 GitHub 仓库获取工作流文件
- 在对应平台（Dify / Flowise / Make 等）中找到「导入工作流」功能
- 上传工作流文件
- 按照提示配置必要的环境变量和 API Key
- 运行测试确认流程正常后投入使用
# 命令行使用
mineecho --help
# 基本用法
mineecho [options] <input>
# Node.js 代码中使用
const mineecho = require('mineecho');
const result = await mineecho.run(options);
console.log(result);
# mineecho 配置说明 # 查看配置选项 mineecho --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 MINEECHO_CONFIG="/path/to/config.yml"
MineEcho
A local-first Memory OS for personal AI assistants: remember, learn, use skills, and spend fewer tokens.
MineEcho is a source-available, local-first AI assistant framework for building private, extensible assistant workflows on top of local services and user-owned knowledge.
MineEcho is not meant to be just another chat UI. Its product loop is:
Remember user preferences and past work. Learn from imported knowledge through Wiki++ and graph context. Use skills and external AI apps through one routing surface. Save context cost with TokenLess reducers and local metrics.
Use MineEcho when a normal chat UI is too forgetful, a RAG app is too passive, and an agent framework is too noisy to run as a long-term personal assistant.
Current Capabilities
- Local console and BFF for chat, skills, memory, knowledge base, calendar/meeting helpers, and configuration.
- Skill center with JSON skill import, ZIP/.skill package import, URL install, AI app registration, trigger refresh, and routing preview APIs.
- AI app adapters that convert RAG/workflow apps into Gateway-callable skills.
- Memory-to-knowledge alignment preview, commit history, and knowledge graph refresh hooks.
- Knowledge graph neighborhood API for explaining selected nodes and one-hop relationships.
- TokenLess compression metrics with local persistence.
Core Highlights
Option 1: Windows Desktop Installer
Download the desktop packages from Baidu Netdisk and choose the Windows installer:
- Link: <https://pan.baidu.com/s/1oERH-NdpTRwobfp1F8keEQ?pwd=j6kd>
- Extraction code:
j6kd
Steps:
- Download the installer package from the link above.
- Run
MineEcho Setup 1.0.0.exeon Windows 10 or Windows 11. - Follow the installer prompts.
- Launch MineEcho from the desktop shortcut or Start menu.
- Complete the first-run setup wizard and configure your model provider API key in Settings.
Notes:
- The Windows installer already includes the MineEcho desktop app and bundled local runtime dependencies required by the packaged version.
- Real model provider API keys are not bundled. Configure your own key locally after first launch.
- Runtime data, chat history, local skills, knowledge files, and provider settings are stored on the user's machine.
Quick Start
Choose one of the following paths:
- Windows desktop installer: recommended for non-developers who want to try MineEcho quickly.
- macOS DMG: recommended for macOS users who want an out-of-the-box desktop package.
- Source startup: recommended for developers who want to inspect, modify, or run the project from source.
cp apps/console/.env.example apps/console/.env
MineEcho does not ship real model API keys. You can start without keys first, then configure model providers in the Console settings page.
#### 5. Start development services
The development URLs are:
- Console: `http://127.0.0.1:5175/`
- BFF: `http://127.0.0.1:3085/`
The checked-in Vite dev config proxies `/api` to the local BFF.
On first launch, open the Console and complete model/API key configuration in Settings. Keep real provider keys in local `.env` files or local Console settings, not in Git.
#### 6. Debug BFF or Console separately
You can start the two apps separately when debugging one side:
#### 7. Verify and build
Build checks:
Start the built BFF package:
Full verification:
Runtime smoke check, after `npm run dev` is running:
Dependency audit for release-blocking advisories:
Export a filtered source tree for public release:
The export command writes to releases/mineecho-source-<version>/ and checks that local runtime data, .env files, databases, keys, logs, and cache artifacts are not included. Publish from the export directory or a fresh clone, not from a local development tree.
cp apps/console/.env.example apps/console/.env
```
Then edit .env locally. Keep any real tokens or service credentials out of commits.
Local development does not force the console login screen by default. Set VITE_MINEECHO_AUTH_REQUIRED=true when you need to test the auth flow explicitly.
The BFF defaults to port 3085. Override it with BFF_PORT only if you also update the Console proxy target.
The following runtime directories are intentionally ignored and should stay out of source control:
.mineecho/.openclaw/apps/**/.mineecho/apps/**/.openclaw/apps/**/workspace/
MineEcho reuses Gateway-related packages from the OpenClaw PI framework in parts of the backend. Those names can appear in protocol adapters, package names, and config-file compatibility code; they are implementation details, not user-facing product branding.
The repository includes vendor/openclaw-gateway/, a vendored copy of the OpenClaw Gateway runtime source from openclaw@2026.5.27 under the upstream MIT license. node_modules are not committed; npm run install:apps installs the Gateway runtime's third-party dependencies locally.
For a more detailed file-by-file map, see docs/runtime-data.md.
Product Screenshots
Model and Runtime Settings
Option 2: macOS DMG
Download the desktop packages from Baidu Netdisk and choose the macOS DMG package:
- Link: <https://pan.baidu.com/s/1oERH-NdpTRwobfp1F8keEQ?pwd=j6kd>
- Extraction code:
j6kd
Steps:
- Download the DMG package from the link above.
- Open the DMG and drag MineEcho into Applications.
- Launch MineEcho from Applications or Launchpad.
- Complete the first-run setup wizard and configure your model provider API key in Settings.
Notes:
- The macOS DMG already includes the MineEcho desktop app and bundled local runtime dependencies required by the packaged version.
- The current macOS package is ad-hoc signed and not Apple Developer ID notarized. On first launch, if macOS blocks the app, open System Settings -> Privacy & Security and click Open Anyway, or right-click MineEcho and choose Open.
- Real model provider API keys are not bundled. Configure your own key locally after first launch.
- Runtime data, chat history, local skills, knowledge files, and provider settings are stored on the user's machine.
Option 3: Source Startup
This is the full path for first-time users who want to run MineEcho from source.
1. Prepare your machine
Install:
- Git
- Node.js 22 or later
- npm, usually bundled with Node.js
Check versions:
git --version
node -v
npm -vIf node -v is lower than 22, upgrade Node.js first.
2. Clone the repository
git clone https://github.com/Health-Yang/MineEcho.git
cd MineEcho3. Install dependencies
npm run install:appsThis installs dependencies for BFF, Console, and the vendored OpenClaw Gateway runtime under vendor/openclaw-gateway. MineEcho ships the OpenClaw Gateway runtime source in this repository, so users do not need to install OpenClaw separately.
4. Create local environment files
```sh cp apps/bff/.env.example apps/bff/.env
Optional, only when you need to override Console defaults:
Optional:
Meeting Workflow
MineEcho是一个创新性的开源AI工作流项目，具有较高的潜力和应用价值
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 分块大小建议 256-512 tokens，向量库优选 pgvector 或 Qdrant
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- embedding 模型与查询模型不一致导致检索失效
- Docker：MineEcho 提供官方镜像，docker compose up 一键启动
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 分块大小建议 256-512 tokens，向量库优选 pgvector 或 Qdrant
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- embedding 模型与查询模型不一致导致检索失效
👥 适合人群
🎯 使用场景
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
- +大幅减少重复性人工操作
- +可视化流程，清晰直观
- +可扩展性强，支持复杂场景
- −初始配置和调试需投入一定时间
- −强依赖外部服务的稳定性
- −复杂场景需具备一定技术基础
该工具使用 NOASSERTION 协议，商用场景请仔细阅读协议条款，必要时咨询法律意见。
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。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
🔗 相关工具推荐
❓ 常见问题 FAQ
经综合评估，MineEcho 在Agent工作流赛道中表现稳健，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 | MineEcho |
| 原始描述 | 开源AI工作流：Local-first Memory OS for personal AI assistants with L0-L3 memory, Wiki++ knowl。⭐128 · TypeScript |
| Topics | ai-agentai-assistantknowledge-graphlocal-firstmemory |
| GitHub | https://github.com/Health-Yang/MineEcho |
| License | NOASSERTION |
| 语言 | TypeScript |
收录时间：2026-06-05 · 更新时间：2026-06-06 · License：NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。