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Sonicmatch

作者:js713-lab版本 0.2.0i★ –i在你的电脑上运行
注册名称io.github.js713-lab/sonicmatch-mcp

安装

概览

作者提供的说明(英文原文)

Analyze video mood and pace, then recommend license-safe BGM with a mix spec.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 设计、图片与音频
  • 你需要填写:GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

运行前请先填写空着的值。

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • GEMINI_API_KEY 机密 env
    Optional. Gemini video understanding for analyze_video_music.
  • JAMENDO_CLIENT_ID 机密 env
    Optional. Jamendo catalog search.
  • FREESOUND_API_KEY 机密 env
    Optional. Freesound beds and loops.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 js713-lab 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2797 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2797 个服务器的 31% 更新
  • 基础检查结果等于或优于此分类中其他 2797 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Sonicmatch 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.0)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。

有什么可以替代它?

同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Figma Context MCP

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

作者:GLips广泛使用↓ 16.1万/周★ 1.6万5个月前更新

在你的电脑上运行

Claude Real Video

Let any LLM watch a video locally — and search everything it has ever watched.

作者:HUANGCHIHHUNGLeo广泛使用↓ 1106/周★ 22842个月前更新

在你的电脑上运行

Figma MCP Server

The Figma MCP server brings Figma design context directly into your AI workflow.

作者:figma广泛使用★ 215213个月前更新

在云端运行✓ mcp.figma.com

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Sonicmatch

Video-native MCP server for license-safe BGM. Watches the footage — not the script — and returns a shortlist, a 12–20s hook, and an ffmpeg ducking spec.

Package / CLI: sonicmatch-mcp. A Model Context Protocol server for Claude Desktop, Cursor, Codex, and other MCP clients. Drop an Instagram Reel, YouTube Short, or TikTok-style clip. Get royalty-free / Creative Commons matches with the license printed on every row.

Video-to-BGM already exists. The wedge is not “I also match music”:

  • it watches the footage, not the script
  • it returns a hook window + ffmpeg ducking spec
  • it is agent-native
  • it prints the license instead of lying

Catalog quality will kill or save this. More tools will not.

Video or URL in

→ scene / mood / pace / speech analysis → license-safe BGM shortlist

  • beat/cut hints
  • optional mix preview

Do not treat this as “script in → YouTube Music search out.” That already exists (mcp-bgm-recommender). Sonicmatch watches the video.

You ownYou do not own
Local file / public URL ingestPlatform music licenses
Mood, energy curve, speech vs silence, scene cutsMeta/TikTok “trending audio” graph
CC / royalty-free catalogs + optional paid adaptersSpotify / IG official libraries
Ranked tracks, preview URLs, mix spec, ffmpegAuto-publish to Instagram

North star: ingest_video → analyze_video_music → recommend_bgm → preview_mix → export_mix_spec

License warning (read this)

  • The code is MIT.
  • Every track has its own license. It is printed on every recommendation.
  • Nothing here is an official Instagram sticker, TikTok Commercial Music Library track, or YouTube Audio Library API result.
  • Do not recommend commercial pop unless the adapter is explicitly a user-owned licensed library.
  • CC-BY still needs attribution. CC-BY-NC is not ok for ads / shops. Non-commercial tracks are never auto-recommended.
  • For ads / shops, wire a user-owned Artlist / Epidemic JSON (examples/user_library.example.json). Do not scrape those sites.
  • Content ID can still hit you if you point at the wrong source. A CC label is not a waiver.

Demo

I dropped ./clip.mp4. Analyze it for an Instagram Reel and recommend 5 instrumental BGMs. Then mix the top pick with ducking and give me the ffmpeg command.

That prompt is the product. Install below, wire Claude Desktop, Cursor, or Codex, and paste it.

Quick start

Requires Python 3.10+ and ffmpeg / ffprobe on PATH. yt-dlp is optional and off by default (SONICMATCH_ALLOW_YTDLP=0) because platform extractors break and may violate ToS. Prefer a local file.

The PyPI project is sonicmatch-mcp. The console script is sonicmatch-mcp, which is what uvx and pipx run. python -m sonicmatch is the same server. The PyPI badge stays empty until the first tag is published. Install from git until then. Maintainer steps: PUBLISH.md.

Works today (git)
uvx --from git+https://github.com/js713-lab/sonic-match-mcp.git sonicmatch-mcp
pip install git+https://github.com/js713-lab/sonic-match-mcp.git

sonicmatch-mcp --version # or: python -m sonicmatch --version

After the first PyPI release
uvx sonicmatch-mcp

or

pipx install sonicmatch-mcp sonicmatch-mcp --version

From a clone (editable + tests)
git clone https://github.com/js713-lab/sonic-match-mcp.git

cd sonic-match-mcp python3 -m venv .venv source .venv/bin/activate pip install -e ".[dev]" cp .env.example .env # optional keys

stdio (Claude Desktop / Cursor / Codex)

sonicmatch-mcp

streamable HTTP (web editors). No authentication. Keep it on loopback.

sonicmatch-mcp --http --port 8765

# same clone, uv

uv venv && uv pip install -e ".[dev]" uv run sonicmatch-mcp

pytest          # generates tiny color mp4s with ffmpeg

ruff check src tests

The seed catalog is about 20 Reel-editor rows (cafe, product, talking-head, travel, food, fashion, event) plus a vocal fixture and a CC-BY-NC fixture. It runs without API keys. Gemini, Jamendo, and Freesound are optional and degrade with a note in the tool response. Seed rows have no hosted audio on purpose — preview_mix synthesizes a demo bed. For real ads, point SONICMATCH_LIBRARY_PATH / EPIDEMIC_LIBRARY_PATH / ARTLIST_LIBRARY_PATH at JSON you already licensed.

VariableRequiredWhat it does
GEMINI_API_KEYnoGemini video understanding for analyze_video_music
JAMENDO_CLIENT_IDnoJamendo search
FREESOUND_API_KEYnoFreesound beds and loops
SONICMATCH_LIBRARY_PATHnoUser-owned library JSON. Also EPIDEMIC_LIBRARY_PATH, ARTLIST_LIBRARY_PATH
SONICMATCH_ALLOW_YTDLPno1 turns on platform URL ingest. Default 0
SONICMATCH_MAX_DOWNLOAD_MBnoDownload cap. Default 200
SONICMATCH_HTTP_HOST / SONICMATCH_HTTP_PORTno--http bind. Default 127.0.0.1:8765

Features

  • Watches the picture. Gemini video understanding when GEMINI_API_KEY is set; otherwise local ffmpeg / audio heuristics (optional Whisper, PySceneDetect, librosa).
  • License on every row. CC / royalty-free / user-owned library. Non-commercial tracks are never auto-recommended. Generated beds stay out of auto recs.
  • Editor-shaped output. 12–20s hook in/out, speech ducking, ffmpeg recipe, mix spec for CapCut / Premiere / DaVinci / your agent.
  • Agent-native MCP. stdio for Claude Desktop and Cursor; streamable HTTP for web editors. Never ships raw multi-MB video through the payload — you get an asset_id.
  • Works without API keys. 20-track seed catalog for Reels. Optional Jamendo, Freesound, and user-owned Artlist / Epidemic JSON.
  • Cuts on the beat. suggest_cuts snaps scene cuts to a BPM grid and returns EDL-ish intro / peak / outro.
  • Brand lock. Save BPM / mood / no-vocals kits and pass brand_kit=… into recommend_bgm.
  • Series, not one-offs. analyze_batch (max 20) clusters mood and returns one shared mini-playlist.
  • Honest about closed graphs. No fake “trending audio,” official IG stickers, or Content-ID-safe stamps. yt-dlp platform ingest is opt-in.

Tools

ToolWhat it does
statusffmpeg / keys / seed count / day-1 risk gates
ingest_videoLocal path or HTTPS URL → asset_id (never video bytes). Platform URLs need SONICMATCH_ALLOW_YTDLP=1
analyze_video_musicMood, energy curve, speech, scenes, hook window, BPM, search queries
recommend_bgm3–7 ranked tracks + why + license + hook in/out
search_musicFree-text / BPM / mood over seed + optional catalogs
get_trackOne track’s metadata, license, attribution, URLs
preview_mixHook trim, loop, optional ducking → preview files + ffmpeg + mix spec
export_mix_specMix spec + ffmpeg + attribution (no render unless render=true)
suggest_cutsBeat grid, snapped scene cuts, EDL, intro / peak / outro
generate_bedDemo bed marked source=generated. Requires i_understand_not_commercially_cleared=true
save_brand_kitPersist BPM / moods / no-vocals for recommend_bgm(brand_kit=…)
analyze_batchUp to 20 clips → mood cluster + shared mini-playlist

Also ships a prompt template: “Score this video like an IG music sticker.”

Product rules (Instagram-like, not Instagram)
  • Prefer instrumental when speech_coverage > 0.25
  • Recommend a hook window, not the whole song
  • Show why (cuts at 0.8s average, 112 BPM, warm gold hour)
  • Always return license + attribution text
  • 3–7 tracks, not 40
  • User can override mood / genre / no-lyrics / platform / energy
  • Never claim “cleared for Instagram official sticker” unless it actually is

Example

Prompt:

I dropped ./clip.mp4. Analyze it for an Instagram Reel and recommend 5 instrumental BGMs. Then mix the top pick with ducking and give me the ffmpeg command.

The agent should call, in order:

  1. ingest_video with the local path. The result is an asset_id, not video bytes.
  2. analyze_video_music with platform_hint set to instagram_reel.
  3. recommend_bgm with that asset_id and max_results of 5.
  4. preview_mix on the top track with ducking, then export_mix_spec.

A recommendation row carries score, reason, suggested_in_out (the hook), ducking, license_ok_for_platform, and content_id_risk (unknown or likely, never cleared). Seed fixtures include seed_golden_hour_latte (CC0-1.0) and seed_indie_porch_110 (CC-BY-4.0). They have no hosted audio. preview_mix synthesizes a demo bed. CC-BY-NC rows are searchable and are not auto-recommended.

Claude Desktop

claude_desktop_config.json. From git, no clone:

{

"mcpServers": { "sonicmatch": { "command": "uvx", "args": [ "--from", "git+https://github.com/js713-lab/sonic-match-mcp.git", "sonicmatch-mcp" ], "env": { "GEMINI_API_KEY": "", "JAMENDO_CLIENT_ID": "", "FREESOUND_API_KEY": "" } } } }

After a clone, command can be the absolute path of .venv/bin/sonicmatch-mcp. After the PyPI release, args is just ["sonicmatch-mcp"]. Copy-paste files: examples/claude_desktop.mcp.json, examples/claude_desktop.pypi.mcp.json.

Cursor

.cursor/mcp.json (project) or ~/.cursor/mcp.json. From git, no clone — examples/cursor.mcp.json:

{

"mcpServers": { "sonicmatch": { "command": "uvx", "args": [ "--from", "git+https://github.com/js713-lab/sonic-match-mcp.git", "sonicmatch-mcp" ], "env": { "GEMINI_API_KEY": "", "JAMENDO_CLIENT_ID": "", "FREESOUND_API_KEY": "" } } } }

After PyPI, use examples/cursor.pypi.mcp.json (uvx with args ["sonicmatch-mcp"]). From a clone: "command": "uv", "args": ["--directory", "/absolute/path/to/sonic-match-mcp", "run", "sonicmatch-mcp"]. After pip install, "command": "python3", "args": ["-m", "sonicmatch"] works if that interpreter has the package.

Codex

Codex reads ~/.codex/config.toml. The same file is shared with the Codex IDE extension and the ChatGPT desktop app. Works today — examples/codex.config.toml:

[mcp_servers.sonicmatch]

command = "uvx" args = ["--from", "git+https://github.com/js713-lab/sonic-match-mcp.git", "sonicmatch-mcp"]

[mcp_servers.sonicmatch.env] GEMINI_API_KEY = "" JAMENDO_CLIENT_ID = "" FREESOUND_API_KEY = ""

Or from the CLI:

codex mcp add sonicmatch -- uvx --from git+https://github.com/js713-lab/sonic-match-mcp.git sonicmatch-mcp

After the PyPI release, the args shrink to sonicmatch-mcp. That file is [`examples/codex.pypi.config.to

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