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Sonicmatch

by js713-labversion 0.2.0i★ –iRuns on your computer
Registry nameio.github.js713-lab/sonicmatch-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Design, images & audio
  • You need to fill in: GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Download the maker’s .mcpb file

The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.

Run this in your terminal

Fill in the empty values before running it.

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

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

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account js713-lab, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

  • More stars than 0% of the other 2794 servers in this category
  • Published to the registry more recently than 31% of the other 2794 servers in this category
  • Basic checks equal to or better than 100% of the other 2794 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Sonicmatch safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GEMINI_API_KEY, JAMENDO_CLIENT_ID, FREESOUND_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.0) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

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

by GLipsWidely used↓ 161.2K/wk★ 16.2KUpdated 5 months ago

Runs on your computer

Claude Real Video

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

by HUANGCHIHHUNGLeoWidely used↓ 1.1K/wk★ 2.3KUpdated 2 months ago

Runs on your computer

Figma MCP Server

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

by figmaWidely used★ 2.2KUpdated 13 months ago

Runs in the cloud✓ mcp.figma.com

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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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