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Minutes会议记录助手

基于 Rust · 让 AI 助手直接操作你的系统与工具
英文名:minutes
⭐ 1.2k Stars 🍴 124 Forks 💻 Rust 📄 MIT 🏷 AI 8.2分
8.2AI 综合评分
会议记录语音转文字知识库MCP协议AI搜索
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,Minutes会议记录助手 获评「强烈推荐」。已获得 1.2k 颗 GitHub Star,这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.2 分,适合有一定技术背景的用户使用。

📚 深度解析
Minutes会议记录助手 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 Minutes会议记录助手,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。Minutes会议记录助手 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 Minutes会议记录助手 评为 AI 评分 8.2 分,属于同类工具中的优质选择。
📋 工具概览

Minutes会议记录助手 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 1.2k
开发语言
Rust
支持平台
Windows / macOS / Linux
维护状态
正常维护,社区驱动
开源协议
MIT
AI 综合评分
8.2 分
工具类型
MCP工具
Forks
124
📖 中文文档
以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

Minutes会议记录助手 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/silverstein/minutes

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "minutes------": {
      "command": "npx",
      "args": ["-y", "minutes"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 Minutes会议记录助手 执行以下任务...
Claude: [自动调用 Minutes会议记录助手 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "minutes______": {
      "command": "npx",
      "args": ["-y", "minutes"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 95/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

minutes

GitHub stars License: MIT

Open-source conversation memory.   useminutes.app

Agents have run logs. Humans have conversations. minutes captures the human side — the decisions, the intent, the context that agents need but can't observe — and makes it queryable.

Record a meeting. Capture a voice memo on a walk. Ask Claude "what did I promise Sarah?" — and get an answer. Your AI remembers every conversation you've had.

Minutes is not just a meeting-notes app. It is local conversation infrastructure for agents: audio capture, transcripts, decisions, commitments, people, and provenance exposed through plain files, CLI commands, MCP tools, and live transcript streams.

Own every conversation you've ever had. Cloud meeting tools rent your own conversations back to you. Minutes writes every meeting to ~/meetings/ as plain markdown, which every AI you use (Claude Code, Codex, Gemini CLI, Cursor, OpenCode, Pi) reads directly. No SDK. No API key. No vendor to outlive. Ten years from now, grep still works on your corpus.  For agents →  ·  Frontmatter schema →

<p align="center"> <img src="docs/assets/demo.gif" alt="minutes demo — record, dictate, phone sync, AI recall" width="750"> </p>

Features

Any platform — from source (requires Rust + cmake; Windows also needs LLVM)

cargo install minutes-cli # macOS/Linux cargo install minutes-cli --no-default-features # Windows (see install notes below)

Or use Mistral API (requires MISTRAL_API_KEY)

[summarization] engine = "mistral" mistral_model = "mistral-large-latest"

Or from source (requires Rust + cmake)

export CXXFLAGS="-I$(xcrun --show-sdk-path)/usr/include/c++/v1" cargo install --path crates/cli ```

Requires (1) parakeet.cpp installed (https://github.com/Frikallo/parakeet.cpp)

Set your name (required for Levels 0-2)

Setup (one-time)

Step 1: Create a sync folder — pick one that syncs between your phone and desktop:

```bash

First-time install

claude plugin marketplace add silverstein/minutes claude plugin install minutes

Install

Download pre-built binary from GitHub releases, or build from source:

Requires: Rust, cmake, MSVC build tools, LLVM (for libclang)

Install LLVM (needed by whisper-rs bindgen):

winget install LLVM.LLVM [Environment]::SetEnvironmentVariable("LIBCLANG_PATH", "C:\Program Files\LLVM\bin", "User")

Full build (includes speaker diarization):

cargo install --path crates/cli

Apple Metal (macOS) — already enabled in the release DMG; use this for source builds

cargo install --path crates/cli --features metal

Setup (all platforms)

```bash

Install ffmpeg for best transcription quality (strongly recommended for non-English audio)

brew install ffmpeg # macOS

apt install ffmpeg # Linux

AND (2) a Minutes CLI compiled with `--features parakeet`. The downloadable

CLI (`brew install silverstein/tap/minutes`) and bare `cargo install minutes-cli`

do not. See docs/PARAKEET.md for the source-build walkthrough.

minutes setup --parakeet # Multilingual v3 (tdt-600m, ~1.2GB) minutes setup --parakeet --parakeet-model tdt-ctc-110m # English-only compact model (~220MB)

Also installs native Silero VAD weights for the parakeet.cpp --vad path

macOS — build from source

export CXXFLAGS="-I$(xcrun --show-sdk-path)/usr/include/c++/v1" export MACOSX_DEPLOYMENT_TARGET=11.0 cargo tauri build --bundles app --features parakeet,metal

Windows — build desktop installer from source

cargo install tauri-cli --version 2.10.1 --locked cd tauri/src-tauri cargo tauri build --ci --bundles nsis --no-sign ```

Tagged GitHub releases can include both a Windows NSIS installer as minutes-desktop-windows-x64-setup.exe and a raw desktop binary as minutes-desktop-windows-x64.exe. The installer is currently unsigned, so treat it as an advanced-user / preview distribution surface until Windows signing is added.

The desktop app adds a system tray icon, recording controls, audio visualizer, Recall, and a meeting list window. The current Windows desktop build covers recording, transcription, search, settings, and Recall. Calendar suggestions, call detection, tray copy/paste automation, and the native dictation hotkey remain macOS-only for now.

Release workflow details live in:

For macOS development, use a dedicated signed dev app identity:

  • Production app: /Applications/Minutes.app (com.useminutes.desktop)
  • Development app: ~/Applications/Minutes Dev.app (com.useminutes.desktop.dev)

If you are testing hotkeys, Screen Recording, Input Monitoring, or repeated macOS permission prompts, launch only Minutes Dev.app via ./scripts/install-dev-app.sh. Avoid the repo symlink ./Minutes.app, raw target/ binaries, or ad-hoc local bundles for TCC-sensitive testing.

This repository is open source, so local development does not require the maintainer's Apple signing credentials:

- ./scripts/install-dev-app.sh works with ad-hoc signing by default - for more stable macOS permission behavior across rebuilds, set MINUTES_DEV_SIGNING_IDENTITY to a consistent local codesigning identity - release signing and notarization remain maintainer/release workflows

For dictation, the recommended path is the standard shortcut in the desktop app (Cmd/Ctrl + Shift + D by default). The raw-key path for keys like Caps Lock is available as an advanced option but remains more fragile and permission-heavy.

Privacy: All Minutes windows are hidden from screen sharing by default — other participants on Zoom/Meet/Teams won't see the app. Toggle via the tray menu: "Hide from Screen Share ✓".

Then replace /Applications/Minutes.app with the new build from

parakeet_vocab = "tdt-600m.tokenizer.vocab" # Safer when multiple Parakeet models are installed

vad_model = "silero-v6.2.0" # Silero VAD model (auto-downloaded by setup). Empty = disable.

# Prevents whisper hallucination loops on non-English/noisy audio.

[summarization] engine = "none" # Default: Claude summarizes conversationally via MCP # "auto" = auto-detect an installed agent CLI for pipeline summaries # "agent" = uses your Claude Code, Codex, OpenCode, or Pi subscription (no API key) # "ollama" = local, free # "openai-compatible" = OpenRouter, Vercel/Cloudflare gateways, llama.cpp, LM Studio, etc. # "claude" / "openai" = direct API key (legacy) agent_command = "claude" # Which CLI to use when engine = "agent" (claude, codex, opencode, pi, etc.) ollama_url = "http://localhost:11434" ollama_model = "llama3.2" openai_compatible_base_url = "http://localhost:11434/v1" openai_compatible_model = "llama3.2" openai_compatible_api_key_env = "" # Blank means no Authorization header for local endpoints. Desktop cloud endpoints can still use a saved Keychain key without rewriting config.

[diarization] engine = "auto" # "auto" (default — uses pyannote-rs if models downloaded, otherwise skips), # "pyannote-rs" (always on — native Rust, no Python), # "pyannote" (legacy — requires pip install pyannote.audio), # "none" (explicitly disabled)

Building your own agent on Minutes

Minutes is designed as infrastructure for AI agents. Files are the durable substrate; MCP is the active interface; live transcript JSONL and the local event log are the real-time paths. The MCP server is the primary integration surface today:

  • Read meetings: list_meetings, search_meetings, get_meeting return structured JSON
  • Track people: get_person_profile builds cross-meeting profiles with topics, open commitments
  • Monitor consistency: consistency_report flags conflicting decisions and stale commitments
  • Record + process: start_recording, stop_recording, process_audio for pipeline control
  • Live coaching: start_live_transcript, read_live_transcript for real-time mid-meeting access
  • Local event stream: minutes events --follow --since-seq N tails newline-delimited events, including finalized live utterances, for agents that want a durable cursor
  • Voice profiles: list_voices, confirm_speaker for speaker identification workflows
  • Resources: Stable URIs (minutes://meetings/recent, minutes://actions/open) for agent context injection

Any agent framework that speaks MCP can use Minutes as its conversation memory layer — the agent handles the intelligence, Minutes handles the recall.

TypeScript SDK — for direct programmatic access without MCP:

npm install minutes-sdk
import { listMeetings, searchMeetings, parseFrontmatter } from "minutes-sdk";

const meetings = await listMeetings("~/meetings", 20);
const results = await searchMeetings("~/meetings", "pricing");

Built with: Rust, whisper.cpp (transcription), pyannote-rs (speaker diarization), Silero VAD (voice activity detection), symphonia (audio decoding), cpal (audio capture), Tauri v2 (desktop app), ureq (HTTP). Optional: ffmpeg (recommended for non-English audio decoding).

Quick start

```bash

Optional: sidecar metadata

If your phone workflow also saves a .json file alongside the audio (same name, .json extension), Minutes reads it for enriched metadata:

{"device": "iPhone", "source": "voice-memos", "captured_at": "2026-03-24T08:41:00-07:00"}

This adds device and captured_at to the meeting's frontmatter. Works with any automation tool (Apple Shortcuts, Tasker, etc.).

Supports .m4a, .mp3, .wav, .ogg, .webm. Format conversion is automatic — uses ffmpeg when available (recommended for non-English audio), falls back to symphonia.

If a desktop call capture leaves a raw file under ~/.minutes/native-captures/, process that audio file directly with minutes process <path> --type meeting. For compatibility, minutes import <audio-file> also routes to the same meeting-processing path; minutes import granola remains the Granola history importer.

Optional: automated summarization

```toml

Desktop users can paste cloud gateway keys in Settings; Minutes stores them

shared config. CLI users can set any env var and name it below. Local servers

Optional: knowledge base integration

Maintain a living knowledge base from your conversations — person profiles, decision history, and a chronological log that compounds over time. Inspired by Karpathy's LLM Wiki pattern.

[knowledge]
enabled = true
path = "~/wiki"        # or your Obsidian vault, PARA system, etc.
adapter = "wiki"       # "wiki" (flat markdown), "para" (atomic facts), "obsidian" (wiki + [[links]])
engine = "none"        # "none" = structured YAML only (safest), "agent" = LLM extraction
min_confidence = "strong"

After each meeting, structured facts (decisions, action items, commitments) flow into person profiles automatically. Every fact carries provenance back to its source meeting.

minutes ingest --dry-run --all   # Preview what would be extracted
minutes ingest --all              # Backfill existing meetings
minutes ingest ~/meetings/call.md # Process a single meeting

Three output formats: - Wikipeople/{slug}.md with facts grouped by category - PARAareas/people/{slug}/items.json with atomic facts (id, status, supersededBy) - Obsidian — Wiki format with [[wikilinks]] for cross-references

Safety: default engine = "none" extracts only from parsed YAML frontmatter. No LLM call, zero hallucination risk. Confidence thresholds filter speculative facts. Corrupt data is backed up, never silently destroyed.

Restart your terminal after setting LIBCLANG_PATH

produce loops on non-English audio. ffmpeg is optional but recommended.

Enable speaker diarization (optional, ~34MB ONNX models)

minutes setup --diarization

In your config file (`$XDG_CONFIG_HOME/minutes/config.toml` when set,

otherwise `~/.config/minutes/config.toml`):

[identity] name = "Your Name"

Configuration

Optional — minutes works out of the box.

```toml

By default: ~/.config/minutes/config.toml

Or: $XDG_CONFIG_HOME/minutes/config.toml when XDG_CONFIG_HOME is set

[transcription] engine = "whisper" # "whisper" (default), "parakeet" (opt-in, lower WER), or "apple-speech" (experimental) model = "small" # whisper: tiny (75MB), base, small (466MB), medium, large-v3 (3.1GB)

engine = "apple-speech" # Experimental: standalone `minutes live` only. Configure via config file or CLI, not desktop settings.

macOS — CLI only

brew tap silverstein/tap && brew install minutes

CLI only (terminal recording, search, vault sync)

brew tap silverstein/tap brew install minutes

DMG and tagged CLI release binaries include the feature; the Homebrew Formula

macOS CLI (Homebrew)

brew upgrade silverstein/tap/minutes

Phone → desktop voice memo pipeline

No phone app needed. Record a thought on your phone, and it becomes searchable memory on your desktop. Claude even surfaces recent memos proactively — "you had a voice memo about pricing yesterday."

The watcher is folder-agnostic — it processes any audio file that lands in a watched folder. Pick the sync method that matches your setup:

PhoneDesktopSync method
**iPhone****Mac**iCloud Drive (built-in, ~5-30s)
**iPhone****Windows/Linux**iCloud for Windows, or Dropbox/Google Drive
**Android****Any**Dropbox, Google Drive, Syncthing, or any folder sync
**Any****Any**AirDrop, USB, email — drop the file in the watched folder

Claude integration

minutes is a native extension for the Claude ecosystem. No API keys needed — Claude summarizes your meetings when you ask, using your existing Claude subscription.

You: "Summarize my last meeting"
Claude: [calls get_meeting] → reads transcript → summarizes in conversation

You: "What did Alex say about pricing?"
Claude: [calls search_meetings] → finds matches → synthesizes answer

You: "Any open action items for me?"
Claude: [calls list_meetings] → scans frontmatter → reports open items

Claude Code (Plugin)

Install the plugin from the marketplace: ```bash

Browser-based integrations such as Google Meet are opt-in on purpose.

Alternative: use Parakeet engine (opt-in, local GPU via parakeet.cpp)

Troubleshooting

No speech detected / blank audio: The most common cause is microphone permissions. Check System Settings → Privacy & Security → Microphone and ensure your terminal app (or Minutes.app) has access.

tmux users: tmux server runs as a separate process that doesn't inherit your terminal's mic permission. Either run minutes record from a direct terminal window (not inside tmux), or use the Minutes.app desktop bundle which gets its own mic permission.

Build fails with C++ errors on macOS 26+: whisper.cpp needs the SDK include path. Set CXXFLAGS as shown above before building.

Dictation hotkey still fails after you enabled it in System Settings: The native hotkey uses macOS Input Monitoring, which is separate from Screen Recording. The fastest way to test the exact installed desktop identity is:

./scripts/diagnose-desktop-hotkey.sh "$HOME/Applications/Minutes Dev.app"

Use ./scripts/install-dev-app.sh first so you are testing the stable development app identity rather than a raw target/ build. The helper intentionally launches the app through LaunchServices; direct shell execution of Contents/MacOS/minutes-app --diagnose-hotkey can misreport TCC status.

🇨🇳 中文文档镜像 AI 翻译 2026-05-24
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介

minutes 是一个开源的会话记忆项目,旨在捕捉人类的决策过程和对话。它提供了一个开放的 API,允许开发者创建自己的应用和集成。

⚡ 功能介绍

minutes 的功能包括捕捉人类决策过程、对话和会议记录,提供自动化的会议总结功能,以及与 Claude 集成的能力,允许开发者创建自己的应用和集成。

📋 环境依赖

minutes 可以在任何平台上运行,包括 Windows、macOS 和 Linux,需要 Rust 和 cmake 运行环境。它还支持使用 Mistral API 和 Claude 集成。

🛠 安装步骤(Docker/pip/源码)

安装 minutes 可以通过使用 Docker、pip 或源码进行部署。具体步骤包括创建一个同步文件夹、安装 minutes-cli 和配置环境变量。

🚀 使用教程

使用 minutes 可以通过 CLI 或 GUI 方式进行操作。CLI 方式包括创建会议记录、搜索会议记录和同步会议记录等功能。GUI 方式包括创建会议记录、查看会议记录和配置环境变量等功能。

⚙️ 配置说明(含 MCP / env)

minutes 支持配置文件和环境变量的使用。配置文件可以用于配置 minutes 的行为和环境变量可以用于配置 minutes 的环境。例如,配置文件可以用于配置 minutes 的自动化总结功能和环境变量可以用于配置 minutes 的 Claude 集成。

🔌 API 说明

minutes 提供了一个 API,允许开发者创建自己的应用和集成。API 支持 RESTful 风格的接口和 JSON 数据格式。

🔄 工作流/模块

minutes 的工作流包括手机端和桌面端的会议记录流程。手机端可以通过 voice memo 录制会议记录,桌面端可以通过 minutes-cli 或 GUI 方式操作会议记录。minutes 还支持 Claude 集成,允许开发者创建自己的应用和集成。

❓ FAQ 摘要

minutes 的常见问题包括没有检测到语音、空白音频和 tmux 用户的问题。解决这些问题的方法包括检查麦克风权限、检查系统设置和配置环境变量等。

🎯 aiskill88 AI 点评 A 级 2026-05-20

优质开源MCP工具,Rust高性能实现,会议转知识库方案实用。社区活跃,持续维护,值得采用。

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 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
  • 做语音类 AI 产品的开发者
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 本地部署优先选 GGUF 量化模型,节省显存并保持响应速度
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
部署方案
  • CLI:直接 npm install -g / pip install,命令行调用
  • 本地部署:CPU 8GB 起,GPU 推荐 16GB+ 显存
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
minutes 中文教程minutes 安装报错怎么办minutes MCP 配置minutes Agent 工作流minutes 与同类工具对比minutes 最佳实践minutes 适合谁用
⚡ 核心功能
👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 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
  • 做语音类 AI 产品的开发者
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 本地部署优先选 GGUF 量化模型,节省显存并保持响应速度
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
👥 适合人群
Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师
🎯 使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
⚖️ 优点与不足
✅ 优点
  • +MIT 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

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。

📄 License 说明

✅ 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。

🔗 相关工具推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合
❓ 常见问题 FAQ
minutes 是一款Rust开发的AI辅助工具。开源MCP工具:Every meeting, every idea, every voice note — searchable by your AI. Open-source。⭐1.2k · Rust 主要应用场景包括:团队会议管理、语音笔记转录、知识库构建。
💡 AI Skill Hub 点评

AI Skill Hub 点评:Minutes会议记录助手 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,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。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 Minutes会议记录助手
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 minutes
原始描述 开源MCP工具:Every meeting, every idea, every voice note — searchable by your AI. Open-source。⭐1.2k · Rust
Topics 会议记录语音转文字知识库MCP协议AI搜索
GitHub https://github.com/silverstein/minutes
License MIT
语言 Rust
🔗 原始来源
🐙 GitHub 仓库  https://github.com/silverstein/minutes 🌐 官方网站  https://useminutes.app

收录时间:2026-05-20 · 更新时间:2026-05-21 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。