Flickies

Official registry Media and design

Self-hosted MCP server: video lipsync, face restore, and ffmpeg ops (trim, concat, transcode).

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

OCI package docker.io/psyb0t/flickies:v0.3.17
Claude Code
claude mcp add flickies -- docker run -i --rm docker.io/psyb0t/flickies:v0.3.17
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flickies": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "docker.io/psyb0t/flickies:v0.3.17"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. flickies
  2. What's in the box
  3. Quick start
  4. Auth
  5. Logging
  6. MCP
  7. Hardware ceiling
  8. License posture
  9. Spec-first
  10. Generated clients
  11. Agent integrations
  12. aigate integration
  13. License

flickies

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

👄 LipsyncLatentSync 1.5 (ByteDance, Apache-2.0, default on CUDA) + Wav2Lip / Wav2Lip-GAN (Rudrabha, fast/low-VRAM, behind FLICKIES_ENABLE_NONCOMMERCIAL=1)
🧹 Face restoreGFPGAN v1.4 (TencentARC, Apache-2.0) — chains after Wav2Lip to fix the soft 96×96 mouth crop, or use standalone
⚙️ ffmpeg opsTrim · concat · transcode (incl. gif + fps + codec change) · scale · mux audio · extract audio · thumbnail grid — pure ffmpeg, CPU
📋 Infoffprobe metadata at /v1/video/info — duration, codec, fps, dimensions, bitrate
🔗 MCP serverAll endpoints exposed as MCP tools so function-calling LLMs can drive the pipeline
📜 Spec-firstopenapi.yaml is the single source of truth — server-side Pydantic, Go client, and Python client all regenerated from one file
🐳 Hot-swap eviction + idle unloadOne GPU pool. Different model requested → current model evicted. Idle longer than FLICKIES_IDLE_UNLOAD_SECS (default 600s) → unloaded by the sweeper.

Quick start

docker run -d --name flickies \
  -v $HOME/flickies-data:/data \
  -p 8000:8000 \
  psyb0t/flickies:latest

curl -s -X POST http://localhost:8000/v1/video/info \
  -H "Content-Type: application/json" \
  -d '{"file_path": "uploads/clip.mp4"}' | jq

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:

engineHF repo
wav2lip / wav2lip-ganNekochu/Wav2Lip
S3FD detectorByteDance/LatentSync-1.5 (bundled in auxiliary/)
gfpganleonelhs/gfpgan
latentsync-1.5ByteDance/LatentSync-1.5

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:

docker run -e FLICKIES_AUTH_TOKEN=testme ...
# clients then send: curl -H "Authorization: Bearer testme" ...

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.

EngineLicenseGate
LatentSync 1.5Apache-2.0none
Wav2Lip / Wav2Lip-GANLRS2 non-commercialFLICKIES_ENABLE_NONCOMMERCIAL=1
GFPGANApache-2.0none
ffmpeg / ffprobe (not an engine; standard CPU helper)LGPL (ffmpeg)none

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.

make generate              # regenerate all three (server models + Go client + Python client)
make generate-models       # just server-side Pydantic
make generate-client-go    # just the Go client
make generate-client-python # just the Python client
make generate-check        # CI gate — fail if generated files drift from openapi.yaml

Never hand-edit generated files. Edit openapi.yaml, run make generate, commit everything together.

Generated clients

Go
go get github.com/psyb0t/docker-flickies/pkg/clients/go@latest
import flickies "github.com/psyb0t/docker-flickies/pkg/clients/go"

c, _ := flickies.NewClient("http://localhost:8000")
resp, err := c.PostVideoLipsync(ctx, flickies.VideoLipsyncRequest{...})
Python
pip install "git+https://github.com/psyb0t/docker-flickies.git#subdirectory=pkg/clients/python/flickies-client"
from flickies_client import Client
from flickies_client.api.lipsync import post_video_lipsync
from flickies_client.models import VideoLipsyncRequest

client = Client(base_url="http://localhost:8000")
result = post_video_lipsync.sync(client=client, body=VideoLipsyncRequest(...))

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 plugin marketplace add psyb0t/agents
claude plugin install flickies@psyb0t

Claude Code prompts for the flickies URL and, if auth is enabled, the token — the token is stored in your OS keychain.

Codex
codex plugin marketplace add psyb0t/agents
codex plugin add flickies@psyb0t

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:

openclaw skills install @psyb0t/flickies

For MCP clients that speak local stdio, the @psyb0t/flickies plugin bridges to flickies' /v1/mcp endpoint:

openclaw plugins install clawhub:@psyb0t/flickies

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.

Frequently asked questions

What is Flickies?

Self-hosted MCP server: video lipsync, face restore, and ffmpeg ops (trim, concat, transcode).

How do I install Flickies?

It runs on your machine. In Claude Code: claude mcp add flickies -- docker run -i --rm docker.io/psyb0t/flickies:v0.3.17. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Flickies need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Flickies open source?

Yes. Its code is on GitHub under the WTFPL license.

Who maintains Flickies?

It is published by psyb0t. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.