io.github.js713-lab/sonicmatch-mcp
sonicmatch-mcp
Open-source MCP server that recommends license-safe background music the way Instagram Stories / Reels feel: drop footage, get a shortlist that already matches energy, then pick a 15s hook.
Source: js713-lab/sonic-match-mcp. The installable package and CLI are named sonicmatch-mcp.
This is infrastructure for editors and agents, not another music chatbot.
Video or URL in
→ scene / mood / pace / speech analysis
→ license-safe BGM shortlist
+ beat/cut hints
+ optional mix previewDo not treat this as “script in → YouTube Music search out.” That already exists (mcp-bgm-recommender). Sonicmatch watches the video.
You own | You do not own |
Local file / public URL ingest | Platform music licenses |
Mood, energy curve, speech vs silence, scene cuts | Meta/TikTok “trending audio” graph |
CC / royalty-free catalogs + optional paid adapters | Spotify / IG official libraries |
Ranked tracks, preview URLs, mix spec, ffmpeg | Auto-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. Content ID can still hit you if you point at the wrong source.
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.
pip install git+https://github.com/js713-lab/sonic-match-mcp.git
# or from a clone
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)
sonicmatch-mcp
# streamable HTTP (web editors)
sonicmatch-mcp --http --port 8765With uv:
uv venv && uv pip install -e ".[dev]"
uv run sonicmatch-mcpv0.2 works offline-ish with the checked-in seed catalog. Gemini, Jamendo, and Freesound are optional and degrade with a note in the tool response.
# tests (generates tiny color mp4s with ffmpeg)
pytestExample agent 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.
Claude Desktop
claude_desktop_config.json:
{
"mcpServers": {
"sonicmatch": {
"command": "/absolute/path/to/sonicmatch-mcp/.venv/bin/sonicmatch-mcp",
"args": [],
"env": {
"GEMINI_API_KEY": "",
"JAMENDO_CLIENT_ID": "",
"FREESOUND_API_KEY": ""
}
}
}
}Cursor
.cursor/mcp.json (project) or ~/.cursor/mcp.json:
{
"mcpServers": {
"sonicmatch": {
"command": "uv",
"args": ["--directory", "/absolute/path/to/sonicmatch-mcp", "run", "sonicmatch-mcp"]
}
}
}Copy-paste configs live in examples/claude_desktop.mcp.json and examples/cursor.mcp.json. User-owned Epidemic/Artlist JSON shape: examples/user_library.example.json. Registry metadata: server.json.
HTTP editors can point at http://127.0.0.1:8765/mcp after sonicmatch-mcp --http.
Architecture
flowchart TB
subgraph mcp [MCP Server - FastMCP / Python - stdio + HTTP]
tools[ingest_video / analyze_video_music / recommend_bgm / preview_mix / export_mix_spec / suggest_cuts]
end
tools --> ingest
tools --> brain
tools --> hub
tools --> mixer
ingest[Ingestor<br/>yt-dlp · ffmpeg · ffprobe · URL/file]
brain[Video Brain<br/>Gemini / local VL · librosa · PySceneDetect · Whisper]
hub[Music Hub<br/>seed CC · Jamendo · Freesound · user library · generate]
mixer[Mixer<br/>ffmpeg · ducking · loop/trim · EDL cuts]
hub --> index[Track index<br/>tags + license + embeddings · SQLite · optional LanceDB]Hard rule: never send raw multi-MB video through the MCP payload. Store locally, pass an asset_id. Loopback, file://, and private IPs are rejected (SSRF).
MCP tools
Tool | Input | Output |
| — | ffmpeg / keys / seed count |
| local path or HTTPS URL, |
|
|
| VideoSonic profile |
| profile or | 3–7 ranked tracks + reasons + license + hook in/out |
| free text / bpm / mood | catalog hits |
| id | metadata + license + urls |
|
| preview files + ffmpeg recipe + mix spec |
|
| mix spec + ffmpeg + attribution (no render unless asked) |
|
| beat grid, snapped scene cuts, EDL, intro/peak/outro |
| prompt / bpm / duration + |
|
| BPM / moods / no-vocals | persisted kit name for |
| list of paths/URLs (max 20) | 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 > 0.25Recommend 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
VideoSonic profile
Analysis returns structured JSON, not a paragraph:
{
"duration_sec": 18.4,
"aspect": "9:16",
"content_type": "lifestyle",
"has_speech": true,
"speech_coverage": 0.62,
"existing_music": false,
"overall_mood": ["warm", "playful"],
"energy_mean": 0.62,
"energy_curve": [{"t": 0, "energy": 0.3}, {"t": 4, "energy": 0.8}],
"pacing": "fast-cut",
"scenes": [{"start": 0, "end": 3.2, "description": "cafe exterior", "energy": 0.4}],
"hook_window": [9.0, 15.0],
"suggested_bpm": [95, 118],
"avoid": ["dark cinematic drone", "aggressive trap", "lyrics-dense"],
"search_queries": ["warm acoustic pop instrumental cafe"],
"platform_hint": "instagram_reel",
"analyzer": "local"
}Primary: Gemini video understanding when
GEMINI_API_KEYis set.Fallback: ffmpeg scene cuts + WAV energy / silence / ZCR heuristics. Optional
faster-whisper,scenedetect,librosaif installed (pip install 'sonicmatch-mcp[local-vl]').
Music hub
Pluggable, license-first. v0 ships:
Adapter | When | License reality |
Seed catalog ( | always | CC0 / CC-BY you control |
Jamendo |
| CC, check commercial |
Freesound |
| CC, good for beds/loops not songs |
User library JSON |
| you already licensed it; we do not scrape paid sites |
Generate |
| always |
Ranking (weighted): mood/energy → instrumental if speech → duration/loop → BPM vs cut rate → license fit → tag embedding cosine → user constraints.
Tracks are indexed in SQLite (~/.cache/sonicmatch-mcp/db/tracks.sqlite) with a 24-d tag embedding. If lancedb is installed (pip install 'sonicmatch-mcp[embeddings]'), vectors are also upserted there.
Seed tracks have no remote audio files on purpose (you should host files you actually have the rights to). preview_mix synthesizes a CC0 demo bed so the mixer still runs offline. generate_bed is a catalog-miss fallback and is not cleared for ads.
Docker
docker build -t sonicmatch-mcp .
docker run --rm -p 8765:8765 -v sonic-cache:/data/cache sonicmatch-mcpRoadmap
Freesound adapter (loops / beds)
Tag embeddings in SQLite (+ optional LanceDB extra)
Epidemic Sound / Artlist as user-owned JSON plugins (no scrape)
Beat-grid vs scene-cut suggestions (EDL-ish
suggest_cuts)MCP registry listing (
server.json)Generate tool, marked
source=generated(local demo; swap a real model at your own legal risk)Real CLAP audio embeddings
Official MCP registry listing via GitHub Release MCPB (see PUBLISH.md)
PyPI release
Beat-grid auto-recut of the video itself (not just EDL hints)
Why this can be a good open-source project
Yes if you nail: (1) video-native analysis, (2) license honesty on every row, (3) editor-shaped output (hook in/out, ducking, mix spec).
No if you only wrap YouTube Music search. That is a weekend clone and a copyright magnet.
Day-1 risk gates (enforced in code, not slogans):
Risk | Gate |
Content ID | Every rec/search/get_track includes |
yt-dlp ToS / broken extractors | Platform URL ingest is off unless |
Upload size / SSRF | HTTPS-only remote ingest, no |
“Trending” is a closed Meta graph | Queries for trending/viral/IG audio/TikTok sound return empty + |
Generation-model commercial terms |
|
Use cases
IG Reel / Story · Shopee product clip · YouTube Shorts agent · CapCut/Premiere companion · campus recap · podcast clipper · travel-vlog batch · brand-kit lock (BPM + no vocals) · silent-film / accessibility · multi-agent studio.