Studio State
FreeNot checkedA stateless MCP server for AI film and video production that tracks project state, shot status, and updates, enabling consistent characters and continuity acros
About
A stateless MCP server for AI film and video production that tracks project state, shot status, and updates, enabling consistent characters and continuity across generative video tools.
README
Keep AI-generated characters, locations, and shots consistent across an entire project — by giving Claude (or any MCP client) a single source of truth for where your production stands.
studio-state is a small, stateless Model Context Protocol
server for people producing AI-generated film, video, episodic shows, and animation
with tools like Higgsfield, Runway, Kling, Seedance, nano-banana, Veo, and ElevenLabs.
It reads your project's plain files on every call and answers three questions an AI
filmmaking assistant constantly needs to re-establish:
orient— "Where am I right now?" Project, phase, active episode, budget/spend posture, open blockers, next actions, and the scene index — one call instead of a 50-line copy-paste at the start of every session.get_shot_status— "What's the state of this scene?" Per-shot status (planned / pending / fired / locked / needs-rework / dropped) reconciled from your shot plan, your canonical lock state, and the server's own working notes.update_shot— "Mark this shot fired/locked and attach the generation job + still."
It's the free companion tool to The Studio Method — a complete system for getting consistent characters and zero-retry continuity out of generative video models.
Why this exists
AI generation tools drift. Across a long shoot they hallucinate characters, swap faces, reinvent backgrounds, and contradict your references — and the human becomes the only thing holding continuity together. Most of that pain is state pain: the assistant helping you forgets where the production stands the moment a session resets.
studio-state fixes the state half structurally. Truth lives in your files, not in a
chat history or a server-side database. Every tool call re-reads the files, so it is
crash-proof and always current, and it never mutates your canonical files — the
only thing it writes is its own per-scene shot_status.json sidecar.
What makes it safe
- Read-dominant. 2 of 3 tools are pure reads. The one writer only ever touches a shim-owned sidecar file — your shot plans, render manifests, and state file are never modified.
- Stateless. No server-side store, no daemon state. Kill it mid-call and nothing corrupts (atomic sidecar writes).
- Path-sandboxed. Scene/episode arguments are validated — no path traversal out of your project tree.
- Hardened. Reviewed adversarially across multiple frontier models before release; malformed files return structured errors instead of crashing the assistant.
Quick start
# 1. Python 3.9+ and the MCP SDK
python3 -m pip install "mcp[cli]" # add --break-system-packages if needed
# 2. Try it against the bundled demo project (no setup)
python3 tests/test_acceptance.py # expect: 4/4 checks passed
# 3. Point it at your own project (a folder containing _pipeline/STATE.json + episodes/)
export STUDIO_ROOT="/path/to/your_show"
python3 server.py
Then register it in Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"studio-state": {
"command": "python3",
"args": ["/abs/path/studio-state-public/server.py"],
"env": { "STUDIO_ROOT": "/abs/path/your_show" }
}
}
}
Full walkthrough: INSTALL.md.
Does my project work with this?
studio-state expects a lightweight, file-based project layout:
your_show/
_pipeline/STATE.json # project phase, episode, budget, scenes
episodes/episode_001/scenes/<SCENE>/
phase_04_IRs.json # the shot plan (shot anchors + types)
phase_05_render_manifest.json # canonical lock/render state (optional)
A complete synthetic example ships in examples/demo_project/ — copy its shape to adapt your own pipeline, or adopt the full convention via the paid pack below.
The Studio Method (paid companion)
This tool tracks state. The hard part — getting the same character to render consistently, shot after shot, with near-zero retries — is a method. The Studio Method Starter Pack is the full system: the character/location/camera "bible" templates, the pre-fire ritual, the prompt-assembly formula, and the anti-default doctrine that make generative models hold continuity.
→ Get the Starter Pack: https://dkf2studios.gumroad.com/l/flplx
(Use code EARLY for the launch discount.)
Tools reference
| Tool | Type | Reads | Writes |
|---|---|---|---|
orient |
read | _pipeline/STATE.json |
— |
get_shot_status |
read | scene IRs + render manifest + sidecar | — |
update_shot |
write | scene IRs (to validate) | shot_status.json sidecar only |
Keywords
AI filmmaking · AI video production · generative video pipeline · character consistency · continuity · shot tracking · render manifest · production state · Model Context Protocol · MCP server · Claude Desktop · Higgsfield · Runway · Kling · Seedance · nano-banana · ElevenLabs · AI short film · AI episodic show · previs · session orientation
License
MIT © 2026 DKF2 Studios. Contact: [email protected]
Installing Studio State
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/dkf2studios/studio-state-publicFAQ
Is Studio State MCP free?
Yes, Studio State MCP is free — one-click install via Unyly at no cost.
Does Studio State need an API key?
No, Studio State runs without API keys or environment variables.
Is Studio State hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Studio State in Claude Desktop, Claude Code or Cursor?
Open Studio State on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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