Studio State

What is Studio State?

Studio State is a small, stateless Model Context Protocol (MCP) server for AI film and video production. It reads a project's plain files to answer three questions an AI filmmaking assistant constantly needs to re-establish: orient the session, get shot status, and update a shot. It’s designed for people producing AI-generated film, video, episodic shows, and animation with tools like Higgsfield, Runway, Kling, Seedance, nano-banana, Veo, and ElevenLabs.

How to use Studio State?

Install Python 3.9+ and the MCP SDK (pip install "mcp[cli]"), set the STUDIO_ROOT environment variable to the path of your project folder, then run python3 server.py. Register the server in Claude Desktop via claude_desktop_config.json using the server’s file path and the STUDIO_ROOT environment variable.

Key features of Studio State

• Read-dominant: 2 of 3 tools are pure reads.
• Stateless: no server-side store or daemon state.
• Path-sandboxed: validated scene/episode arguments.
• Crash-proof and always current; re-reads files on every call.
• Never mutates canonical files; writes only to a sidecar shot_status.json.
• Expects a lightweight, file-based project layout.

Use cases of Studio State

• Re-establishing production context at the start of a Claude session.
• Tracking per-shot status (planned, pending, fired, locked, needs-rework, dropped) across an episode.
• Marking a shot as fired or locked and attaching a generation job and still.
• Keeping characters, locations, and shots consistent across a long generative video production.

FAQ from Studio State

What project layout does Studio State require?

It expects a folder with _pipeline/STATE.json (project phase, episode, budget, scenes) and episodes organized as episodes/episode_XXX/scenes/<SCENE>/ containing the shot plan and render manifest files.

Is Studio State safe for my production files?

Yes. It is read-dominant (two of three tools are pure reads). The only writer creates a per-scene shot_status.json sidecar — it never modifies your shot plans, render manifests, or state file. Writes are atomic and path-sandboxed.

What dependencies or runtime are required?

Python 3.9+ and the MCP SDK (mcp[cli]) are required. The server runs as a Python script and communicates via the Model Context Protocol using stdio.

Can I try Studio State before using my own project?

Yes, a bundled demo project is included. Run python3 tests/test_acceptance.py to verify the server works (expects 4/4 checks passed).

What transport or authentication does Studio State use?

The README does not specify OAuth or API-key authentication; it is configured as a local MCP server via Claude Desktop’s stdio transport with an environment variable for the project root.