
Flickies
io.github.psyb0t由 GitHub 账号 psyb0t 发布v0.3.17更新于 Oct 31, 2026
Self-hosted MCP server: video lipsync, face restore, and ffmpeg ops (trim, concat, transcode).
概览
自托管的视频工具 MCP 服务器,提供口型同步、人脸修复以及裁剪、拼接、转码等 ffmpeg 操作。
- 可以做什么
- 用给定音轨对视频做口型同步,并用 GFPGAN 修复或锐化人脸。
- 裁剪、拼接、转码、缩放,以及修改帧率和编码,包括输出 GIF。
- 混流或提取音轨,并生成缩略图网格。
- 读取 ffprobe 元数据,如时长、编码、帧率、分辨率和码率。
- 在运行任务前列出可用引擎及其状态。
- 适用场景
- 适合希望助手在本地完成视频制作或编辑、不依赖云服务的场景,例如给片段配上新音频、修复人脸,或做常规的 ffmpeg 转换与剪辑。适用于可自行运行容器、并通过挂载数据目录共享文件的自托管环境。
- 运行要求
- 以 Docker 容器运行,暴露带 MCP 路径的 HTTP 端点,助手连接该端点,也可通过本地 stdio 桥接插件接入。需要挂载数据目录以存放文件、模型权重和日志;首次使用需联网从 Hugging Face 下载模型权重,除非已离线预置。LatentSync 与 GFPGAN 需要 CUDA GPU,CPU 镜像仅支持 ffmpeg 操作和 Wav2Lip。可选通过 FLICKIES_AUTH_TOKEN 设置 Bearer 令牌。
安装
在 SourceWeft 中
- 打开 控制台中的 Flickies,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
flickies
[CI] [version] [license] [Docker Pulls]
Video toolkit. One port. Zero cloud. Lipsync, face restore, ffmpeg. Fire-and-forget async jobs. Webhooks. Spec-first OpenAPI; typed Go + Python clients generated from the same spec.
The video sibling of audiolla (audio) and talkies (speech). Same wire format, same async-job model, same bind-mount-/data story, same Makefile shape, same :latest + :latest-cuda split, same opt-in non-commercial gate.
POST a JSON body. Get a video back. Drive it from curl, shell scripts, the generated Go/Python clients, or point an LLM agent at the MCP endpoint.
No account. No subscription. docker run and you're done.
What's in the box
Quick start
CUDA image at psyb0t/flickies:latest-cuda runs every engine at usable speed. CPU image runs all ffmpeg ops (trim/concat/transcode incl. gif/scale/mux/extract/thumbnail-grid/info) + Wav2Lip-CPU (~44s for a 3s clip; OK for short ones). GFPGAN + LatentSync 1.5 are CUDA-only — CPU image refuses to load them.
Weights live in the standard HuggingFace cache layout under /data/hf/hub/models--<org>--<name>/{blobs,snapshots,refs}/… — content-addressed blobs, snapshot-named symlinks, reusable by any other HF-aware tool sharing the bind mount (not just flickies). Sources:
Lazy by default — each engine fetches its repo on first request. Set FLICKIES_ENABLED_ENGINES=wav2lip,gfpgan (or FLICKIES_PREFETCH_ALL=1) to pull at boot before uvicorn starts. FLICKIES_OFFLINE=1 disables auto-download (operators stage the snapshot dir manually).
Auth
Bearer token set via env. Any string works:
Unset → auth disabled. /healthz is always probe-exempt.
Logging
Structured JSON to both stderr AND a rotating file at FLICKIES_LOG_FILE (default /data/logs/flickies.log, 50 MB × 5 backups). Every line carries time (ISO 8601 UTC sub-ms), level, logger, file, line, func, msg, trace_id, request_id + typed extras.
Inbound X-Request-Id (UUID v4 OR ULID; garbage → server mints fresh) threads onto the logging scope via ContextVar + echoes back on the response. Outbound httpx fetches forward X-Request-Id + X-Trace-Id so the next hop's logs correlate. Sensitive keys (authorization, cookie, *token*, *secret*, hf_*, sk-ant-*) get [REDACTED] automatically at format time.
Default level is INFO; set FLICKIES_LOG_LEVEL=DEBUG for reconstruction-grade tracing: every ffmpeg/ffprobe command + result, each transform's decision (e.g. trim stream_copy vs precise_reencode) + output size, engine inference timing (wall_secs), URL fetch/upload byte counts, and job lifecycle. Logged URLs are stripped of their query string so presigned credentials never reach the logs.
MCP
Eleven tools at /v1/mcp via streamable-HTTP JSON-RPC: list_engines, info, lipsync, restore, transcode, trim, concat, scale, mux_audio, extract_audio, thumbnail_grid. Point a function-calling LLM at it (LibreChat, Cursor, Claude desktop with the MCP connector) and it drives the pipeline.
Hardware ceiling
Tested target: RTX 3060 12 GB. Fits LatentSync 1.5 (~8 GB) with headroom. Wav2Lip + GFPGAN chain peaks at ~5 GB. One engine resident at a time — different model request triggers hot-swap eviction.
License posture
Wav2Lip variants are trained on LRS2 (non-commercial). The server refuses to load them unless FLICKIES_ENABLE_NONCOMMERCIAL=1 is set in the server env. LatentSync 1.5 (Apache-2.0) is the commercial-safe default — no gate.
Same pattern as audiolla's MusicGen / matchering gates.
Spec-first
Every request/response shape lives in openapi.yaml. The Pydantic models in src/flickies/schema/_generated.py, the Go client in pkg/clients/go/client.gen.go, and the Python client in pkg/clients/python/flickies-client/ are all generated from that single file.
Never hand-edit generated files. Edit openapi.yaml, run make generate, commit everything together.
Generated clients
Go
Python
Agent integrations
The skill works in any agent that reads .agents/skills/ (such as peen), and installs natively in the clients below.
Claude Code
Claude Code prompts for the flickies URL and, if auth is enabled, the token — the token is stored in your OS keychain.
Codex
Installed via the marketplace, the skill invokes as $flickies:flickies. Codex also picks the skill up automatically with no install in any repo containing .agents/skills/, where it invokes as plain $flickies.
OpenClaw
The skill is published to ClawHub on every release:
For MCP clients that speak local stdio, the @psyb0t/flickies plugin bridges to flickies' /v1/mcp endpoint:
Then set FLICKIES_URL (and FLICKIES_AUTH_TOKEN if the server requires one).
aigate integration
Mounts in aigate at /flickies/ and /flickies-cuda/ behind the same nginx → make run-bg lives. FLICKIES=1 and FLICKIES_CUDA=1 toggle the variants.
License
WTFPL for flickies itself. Bundled models follow their upstream licenses — review before commercial redistribution.
来源:README.md,提交 d8b19e5
工具
0版本历史
2- v0.3.17最新Oct 10, 2026
- v0.3.16Sep 16, 2026
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