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io.github.js713-lab/sonicmatch-mcp

by js713-lab
README.md
# Sonicmatch

<!-- mcp-name: io.github.js713-lab/sonicmatch-mcp -->

[![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)
[![GitHub stars](https://img.shields.io/github/stars/js713-lab/sonic-match-mcp?style=flat)](https://github.com/js713-lab/sonic-match-mcp/stargazers)

**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.

<p align="center">
  <img src="docs/banner.jpg" alt="Sonicmatch — video in, license-safe BGM out. Ingest, Analyze, Match, Mix." width="100%">
</p>

Package / CLI: [`sonicmatch-mcp`](https://github.com/js713-lab/sonic-match-mcp). A [Model Context Protocol](https://modelcontextprotocol.io) server for Claude Desktop, Cursor, 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 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. 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 or Cursor, 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.

```bash
pip install git+https://github.com/js713-lab/sonic-match-mcp.git
sonicmatch-mcp            # or: python3 -m sonicmatch
```

With [uv](https://github.com/astral-sh/uv), no clone:

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

From a clone (editable + tests):

```bash
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 8765
```

```bash
# same clone, uv
uv venv && uv pip install -e ".[dev]"
uv run sonicmatch-mcp
```

v0.2 works **offline-ish** with a 20-track seed catalog aimed at Reel editors (cafe, product, talking-head, travel, food, fashion, event). 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.

```bash
pytest   # generates tiny color mp4s with ffmpeg
```

Not on PyPI yet. Install from git.

## 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

| Tool | What it does |
|---|---|
| `status` | ffmpeg / keys / seed count / day-1 risk gates |
| `ingest_video` | Local path or HTTPS URL → `asset_id` (never video bytes). Platform URLs need `SONICMATCH_ALLOW_YTDLP=1` |
| `analyze_video_music` | Mood, energy curve, speech, scenes, hook window, BPM, search queries |
| `recommend_bgm` | 3–7 ranked tracks + why + license + hook in/out |
| `search_music` | Free-text / BPM / mood over seed + optional catalogs |
| `get_track` | One track’s metadata, license, attribution, URLs |
| `preview_mix` | Hook trim, loop, optional ducking → preview files + ffmpeg + mix spec |
| `export_mix_spec` | Mix spec + ffmpeg + attribution (no render unless `render=true`) |
| `suggest_cuts` | Beat grid, snapped scene cuts, EDL, intro / peak / outro |
| `generate_bed` | Demo bed marked `source=generated`. Requires `i_understand_not_commercially_cleared=true` |
| `save_brand_kit` | Persist BPM / moods / no-vocals for `recommend_bgm(brand_kit=…)` |
| `analyze_batch` | Up 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

## Claude Desktop

`claude_desktop_config.json` — after a clone + `pip install -e .`:

```json
{
  "mcpServers": {
    "sonicmatch": {
      "command": "/absolute/path/to/sonic-match-mcp/.venv/bin/sonicmatch-mcp",
      "args": [],
      "env": {
        "GEMINI_API_KEY": "",
        "JAMENDO_CLIENT_ID": "",
        "FREESOUND_API_KEY": ""
      }
    }
  }
}
```

After `pip install git+https://github.com/js713-lab/sonic-match-mcp.git`, `command` can be `sonicmatch-mcp` if that binary is on PATH.

## Cursor

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

```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": ""
      }
    }
  }
}
```

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.

Copy-paste configs: [`examples/claude_desktop.mcp.json`](examples/claude_desktop.mcp.json), [`examples/cursor.mcp.json`](examples/cursor.mcp.json). User-owned Epidemic/Artlist JSON shape: [`examples/user_library.example.json`](examples/user_library.example.json). Registry metadata: [`server.json`](server.json).

HTTP editors can point at `http://127.0.0.1:8765/mcp` after `sonicmatch-mcp --http`.

`--http` has no authentication. Keep it on loopback. The Docker image binds `0.0.0.0` so the container port works — do not publish that port to the internet. See [SECURITY.md](SECURITY.md).

## Architecture

```mermaid
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).

## VideoSonic profile

Analysis returns structured JSON, not a paragraph:

```json
{
  "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_KEY` is set.
- **Fallback:** ffmpeg scene cuts + WAV energy / silence / ZCR heuristics. Optional `faster-whisper`, `scenedetect`, `librosa` if installed (`pip install 'sonicmatch-mcp[local-vl]'`).

## Music hub

Pluggable, license-first. v0 ships:

| Adapter | When | License reality |
|---|---|---|
| **Seed catalog** (`data/seed_tracks.json`) | always | 20 CC0 / CC-BY Reel beds + a vocal fixture + a CC-BY-NC fixture (NC is never auto-recommended) |
| **Jamendo** | `JAMENDO_CLIENT_ID` | CC, check commercial |
| **Freesound** | `FREESOUND_API_KEY` | CC, good for beds/loops not songs |
| **User library JSON** | `SONICMATCH_LIBRARY_PATH` / `EPIDEMIC_LIBRARY_PATH` / `ARTLIST_LIBRARY_PATH` | **you** already licensed it; we do not scrape paid sites |
| **Generate** | `generate_bed` | always `source=generated`; local sine demo unless you swap a real model |

Ranking (weighted): mood/energy → instrumental if speech → duration/loop → BPM vs cut rate → license fit → tag embedding cosine → user constraints. `recommend_bgm` drops non-commercial and generated tracks instead of downranking them.

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

```bash
docker build -t sonicmatch-mcp .
# Loopback-only publish. The process inside the container has no HTTP auth.
docker run --rm -p 127.0.0.1:8765:8765 -v sonic-cache:/data/cache sonicmatch-mcp
```

## Roadmap

Catalog > new tools.

- [x] Freesound adapter (loops / beds)
- [x] Tag embeddings in SQLite (+ optional LanceDB extra)
- [x] Epidemic Sound / Artlist as **user-owned JSON** plugins (no scrape)
- [x] Beat-grid vs scene-cut suggestions (EDL-ish `suggest_cuts`)
- [x] MCP registry listing (`server.json`)
- [x] Generate tool, marked `source=generated` (local demo; swap a real model at your own legal risk)
- [x] Official MCP registry listing via GitHub Release MCPB (see [PUBLISH.md](PUBLISH.md))
- [x] Non-commercial licenses excluded from auto `recommend_bgm`
- [ ] 20 seed beds a Reel editor would actually keep, with audio you host
- [ ] User-owned Artlist / Epidemic JSON as the default path for ads
- [ ] Real CLAP audio embeddings
- [ ] PyPI release

## 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), (4) a catalog someone would keep.

**No if** you only wrap YouTube Music search, or if the first five recs sound like leftover stock beds.

Day-1 risk gates (enforced in code, not slogans):

| Risk | Gate |
|---|---|
| **Content ID** | Every rec/search/get_track includes `content_id_warning`. CC/RF is never "Content-ID-safe". `content_id_risk` is `unknown` or `likely`, never `cleared`. |
| **yt-dlp ToS / broken extractors** | Platform URL ingest is off unless `SONICMATCH_ALLOW_YTDLP=1`. Failures map to `YTDLP_EXTRACTOR` and tell you to pass a local file. |
| **Upload size / SSRF** | HTTPS-only remote ingest, no `file://` / loopback / private IPs, `SONICMATCH_MAX_DOWNLOAD_MB` (default 200) on files, HTTP, and yt-dlp `--max-filesize`. |
| **“Trending” is a closed Meta graph** | Queries for trending/viral/IG audio/TikTok sound return empty + `TRENDING_UNAVAILABLE`. `recommend_bgm` always sets `trending_available=false`. |
| **Generation-model commercial terms** | `generate_bed` refuses unless `i_understand_not_commercially_cleared=true`. Generated tracks are excluded from auto `recommend_bgm`. |

## 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.

## License

MIT. Track licenses are independent of the repo license. Security reports: [SECURITY.md](SECURITY.md).

From [CodeCrafter](https://codecrafter.dev).

<!-- maintainer note 2026-09-16T08:47Z -->

<!-- maintainer note 2026-09-16T08:47Z -->

TDQS

A3.5/5.0

Scored across 12 tools

Disambiguation4/5

Most tools have clearly distinct roles in the pipeline (ingest, analyze, recommend, search, render, export, cuts, bed generation). However, preview_mix and export_mix_spec overlap significantly since export_mix_spec with render=true is explicitly 'same as preview_mix', and recommend_bgm vs search_music both perform music lookup with some boundary overlap.

Naming Consistency4/5

All tools follow the snake_case verb_noun pattern (ingest_video, recommend_bgm, suggest_cuts, save_brand_kit, etc.), except for the noun-only 'status'. That minor inconsistency is the only deviation, making the set predictable.

Tool Count5/5

12 tools map directly to a coherent music-video workflow: video ingest, analysis, BGM recommendation/search, track details, mixing, export, cutting, generated beds, brand kit, and batch analysis. Every tool has a clear purpose and the count fits squarely in the well-scoped range.

Completeness4/5

The toolkit covers the essential lifecycle from video input to analysis, music selection, mix preview, specification export, and batch operation. Minor gaps exist like management of saved assets (e.g., updating brand kits or deleting generated beds), but the core workflow has no dead ends and agents can complete a full pipeline.

Maintenance

ActivityMaintained
ResponsivenessResponsive