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把和弦灵感、吉他把位、实时调音、节拍练习和 AI 编曲放进同一个工作台。
MoChord 不是一个只会画和弦图的小工具。它更像一间面向吉他手的智能练习室:输入一个和弦,马上看到指板、五线谱、六线谱和可播放音色;输入一个调式或级数走向,AI 会生成初学者版与进阶版和弦进行;打开调音器,麦克风信号会经过实时音高检测、滤波、平滑和八度纠偏,帮助你把每一根弦调到更可靠的位置。
如果你正在写歌、练琴、教学、扒歌、做和声实验,MoChord 想解决的是同一个痛点:不要在和弦网站、调音器、节拍器、谱面工具和 AI 聊天窗口之间来回切换。
大多数音乐工具只解决一个动作:查和弦、调音、听音、打节拍、生成灵感。MoChord 的目标是把这些动作串成一个完整创作和练习链路。
你可以从一句非常模糊的想法开始:
D Major 4-5-6-6
C Major 1-5-6-4
G Major I-V-VI-IV
A minor melancholy chorus
MoChord 会把它变成:
这意味着 MoChord 不只是“给你答案”,而是把答案变成你能立刻弹、立刻听、立刻练的材料。
桌面版 MoChord 通过 Tauri/Rust 侧调用 DeepSeek,避免把 API key 暴露在浏览器前端。用户可以在本地 .env 配置密钥,也可以通过应用界面保存密钥;保存后的 key 留在本机。
AI 生成流程会返回结构化 JSON,并经过前端 schema 校验。结果包括:
当 DeepSeek 不可用、返回异常或未配置 key 时,MoChord 会自动进入本地兜底生成流程,根据调式与级数生成可用和弦,不让创作流中断。
MoChord 的 AI 不停在“给一串和弦”。生成结果可以直接进入练习模式,AI Coach 会把和弦变成三轮或多轮练习计划:
这让 AI 结果从灵感文本变成真实可执行的吉他训练。
MoChord 还包含歌曲草稿生成提示词体系,可以根据风格、调性、难度、BPM、拍号、是否生成歌词等参数,生成吉他友好的完整歌曲结构。生成规则要求和弦可解析、段落可练习、歌词原创,并支持中英文输出。
MoChord 的把位系统不是简单查表。它会优先使用用户保存的自定义按法和内置经典按法;当没有现成按法时,会动态生成多把位候选。
算法会在 1 到 12 品范围内搜索可用组合,并对候选按法打分:
最终,MoChord 会把这些候选变成可视化和弦图、六线谱、可播放音高,并允许用户保存自己的按法。保存后的把位会优先生效,适合长期建立个人指法库。
调音器是 MoChord 的硬核模块之一。它直接使用浏览器/桌面运行时的麦克风输入,并关闭回声消除、噪声抑制和自动增益控制,让算法尽量接近原始乐器信号。
信号链路包括:
getUserMedia 捕捉麦克风输入AudioContextAnalyserNode,fftSize = 8192调音器会把检测到的频率转换为 MIDI 音高、音名、目标频率和 cents 偏差。对于吉他场景,MoChord 还会根据当前调弦目标选择最接近的弦和品位,而不是只显示孤立音名。
MoChord 支持可调参考音:
A4 reference: 432Hz - 445Hz
Default: 440Hz
内置调弦:
调音目标会根据参考 A4 重新计算频率,因此同一套调弦可以适配不同乐队、录音或现场环境。
| 模块 | 能力 |
|---|---|
| 和弦工作台 | 输入和弦名,生成和弦结构、指板图、五线谱简图、六线谱和可播放音符 |
| AI 生成器 | 根据调性、调式、级数或自然语言提示生成 beginner/professional 两套进行 |
| 智能把位 | 多把位搜索、评分、排序、指法估计、大横按识别、自定义保存 |
| 音频试听 | Tone.js 播放和弦、扫弦和整段和弦进行 |
| 节拍器 | BPM、拍号、重拍、数拍和练习播放联动 |
| 练习模式 | 当前和弦、下一个和弦、拍点、小节、把位图和调音目标同步显示 |
| 调音器 | 实时音高检测、cents 偏差、输入电平、参考频率和调弦预设 |
| 歌曲编排 | 段落、歌词行和弦、节奏型、重复次数与整首练习 |
| 曲库 | 保存 AI 生成或手动整理的和弦进行 |
| 账号同步 | Supabase 登录、资料、头像、进度同步和访客进度合并 |
| 国际化 | 英文与中文界面文案 |
安装依赖:
npm install
启动 Web 版:
npm run dev
启动桌面版:
npm run desktop:dev
构建 Web 资源:
npm run build
构建桌面应用:
npm run desktop:build
复制环境变量模板:
cp .env.example .env
可配置项:
DEEPSEEK_API_KEY=your_deepseek_api_key_here
DEEPSEEK_BASE_URL=https://api.deepseek.com
DEEPSEEK_MODEL=deepseek-chat
VITE_SUPABASE_URL=your_supabase_project_url
VITE_SUPABASE_ANON_KEY=your_supabase_anon_key
说明:
.env,里面可能包含真实 API key。MoChord 使用 Supabase Auth 和 user_progress 表保存学习与练习进度。
.env。supabase/schema.sql。SQL 会创建:
public.profilespublic.user_progressavatars Storage bucketMoChord 可以通过 Tauri 2 运行在 Android。
初始化 Android 项目:
npm run android:init
开发运行:
npm run android:dev
连接设备运行生产模式:
npm run android:run
构建 Android 产物:
npm run android:build
Android 需要网络权限用于 Supabase/DeepSeek,需要麦克风权限用于调音器。
项目包含多个聚焦测试脚本:
npm run test:tuner-engine
npm run test:practice-mode
npm run test:practice-coach
npm run test:practice-stats
npm run test:practice-voicing-path
npm run test:workspace-state
npm run test:progress-sync
npm run test:ai-generator-language
npm run test:song-draft
npm run test:song-arrangement
这些测试覆盖调音器算法、练习状态、AI 生成语言、歌曲草稿、曲库、同步、把位路径等核心能力。
MoChord 适合:
MoChord 的目标不是替代音乐判断,而是把音乐判断需要的上下文放到同一个界面里:声音、手型、谱面、节奏、频率和 AI 建议互相对齐。
This project is licensed under the MIT License. See LICENSE for details.
Put chord inspiration, guitar voicings, real-time tuning, rhythm practice, and AI-powered arrangement in one focused workspace.
MoChord is more than a chord diagram tool. It is an intelligent practice room for guitar players: type a chord and immediately see the fretboard, staff view, tablature, and playable sound; enter a key, mode, or degree pattern and AI generates beginner-friendly and more advanced chord progressions; open the tuner and the microphone signal is processed through real-time pitch detection, filtering, smoothing, and octave-jump correction so every string lands closer to the target.
If you write songs, practice guitar, teach students, transcribe ideas, or explore harmony, MoChord is built around one simple promise: stop jumping between chord sites, tuners, metronomes, notation tools, and AI chat windows.
Most music tools solve one isolated action: look up a chord, tune a guitar, play a sound, count a beat, or generate an idea. MoChord connects those actions into a complete creative and practice workflow.
You can start with a loose idea:
D Major 4-5-6-6
C Major 1-5-6-4
G Major I-V-IV-IV
A minor melancholy chorus
MoChord turns it into:
MoChord does not just give you an answer. It turns the answer into something you can play, hear, save, and practice immediately.
The desktop version of MoChord calls DeepSeek from the Tauri/Rust side, so the API key is not exposed to frontend browser code. Users can configure a key in a local .env file or save one through the app UI; saved keys stay on the local machine.
The AI workflow returns structured JSON and validates it before use. Results include:
When DeepSeek is unavailable, returns an invalid response, or has no configured API key, MoChord falls back to a local generation path based on mode and degree logic, keeping the creative flow moving.
MoChord's AI does not stop at a chord list. Generated progressions can be sent directly into practice mode, where the AI Coach turns them into a progressive training plan:
That makes each AI result practical rather than merely inspirational.
MoChord also includes a song draft prompt system that can generate guitar-friendly song structures from style, key, difficulty, BPM, time signature, length, and lyric settings. The prompt rules require parseable guitar chords, practice-ready sections, original lyrics, and bilingual output support.
MoChord's voicing system is not just a lookup table. It first respects user-saved custom shapes and built-in classic shapes; when no direct shape is available, it dynamically generates multi-position candidates.
The algorithm searches across frets 1 to 12 and scores candidate shapes by musical and ergonomic quality:
The final candidates become visual chord diagrams, tablature, playable pitches, and selectable saved voicings. Once a user saves a personal shape, MoChord prioritizes it in future sessions.
The tuner is one of MoChord's strongest technical modules. It uses microphone input directly from the browser or desktop runtime and disables echo cancellation, noise suppression, and automatic gain control to keep the signal closer to the raw instrument.
The signal chain includes:
getUserMedia microphone captureAudioContextAnalyserNode with fftSize = 8192The tuner converts detected frequency into MIDI pitch, note name, target frequency, and cents deviation. For guitar use, MoChord also selects the nearest string and fret target from the active tuning context, instead of showing only an isolated note name.
MoChord supports an adjustable reference pitch:
A4 reference: 432Hz - 445Hz
Default: 440Hz
Built-in tunings:
Tuning targets are recalculated from the selected A4 reference, making the same tuning layout adaptable to different bands, recordings, and live contexts.
| Module | Capability |
|---|---|
| Chord workspace | Type a chord and generate chord structure, fretboard diagram, simplified staff view, tab, and playable notes |
| AI generator | Generate beginner/professional progressions from keys, modes, degrees, or natural-language prompts |
| Smart voicings | Multi-position search, scoring, sorting, fingering estimation, barre detection, and custom shape saving |
| Audio audition | Play chords, strums, and full progressions with Tone.js |
| Metronome | BPM, time signature, accents, count-in, and practice playback integration |
| Practice mode | Current chord, next chord, beat, bar, voicing diagram, and tuning target display |
| Tuner | Real-time pitch detection, cents deviation, input level, reference frequency, and tuning presets |
| Song arranger | Sections, lyric-line chords, rhythm pat |
$ claude mcp add MoChord \
-- python -m otcore.mcp_server <graph>