I Connected Claude Code to Seedance, Kling and Veo Through One MCP Server - Here's the Exact Setup

Every AI video tool I use lives in its own tab, with its own subscription, its own credit balance, and its own idea of what my project is.

My script is in one doc. My character references are in a folder. My storyboard — if it exists at all — is a screenshot graveyard. By shot six of a short drama, I am not directing anymore. I am doing data entry between tools that don't talk to each other.

So when we built DramaCanvas, we made two decisions that this post is about:

1. The production workspace is an infinite canvas, not a chat thread — script cards, character references, storyboard frames, generated clips, audio and the timeline all sit in one spatial layout.
2. The canvas is reachable from outside through a remote MCP server, so tools like Claude Code, Codex and Cursor can work on a production with you — and you can bring your own model keys (BYOK) instead of paying a marked-up credit bundle.

Here is the exact setup, the workflow it enables, and the honest limitations.

The setup (about two minutes)

You need a DramaCanvas account and an API key from it. Then, for Claude Code:

claude mcp add --transport http dramacanva https://dramacanva.com/api/mcp --header "Authorization: Bearer $DRAMACANVA_API_KEY"

That's it — it's a remote, streamable-HTTP MCP server, so there is nothing to install, clone or run locally. The same endpoint works for Codex and Cursor: add a remote MCP server with the URL https://dramacanva.com/api/mcp and the same Authorization: Bearer <your key> header.

Once connected, ask your coding agent to list the available tools first. That one habit saves a lot of confusion, because the surface area is a production surface — projects, script and storyboard structures, generation nodes — not a single "make video" button.

What this workflow is actually good for

1. Turning a script into a storyboard structure without clicking 40 times.
Breaking a script into shots is structured, repetitive work: one card per beat, shot type, character action, dialogue line. That's exactly the kind of work an agent does well when it can write into the same canvas you will later generate on. You review and rearrange spatially; the agent does the clerical part.

2. Keeping character consistency a data problem, not a luck problem.
The number one failure mode in AI short drama is character drift: by the third shot, your lead is a stranger. On the canvas, a character's reference images live next to every shot that uses them, and video nodes can pin both the first and the last frame, so the model resolves motion between two fixed realities instead of guessing forward from one. When an agent helps you set up shots, it can reuse the same reference set across all of them — consistency stops depending on you remembering which file you uploaded where.

3. Choosing the model per shot, on one project.
DramaCanvas aggregates models rather than betting on one: Seedance 2.0 / 2.5 (up to 30-second shots and reference video at 1080p on 2.5), Kling 3.0 / 4.0, Veo 3.1, MiniMax H3, Wan 3.0 and Grok Imagine for video; Nano Banana, GPT Image 2 and Midjourney V7 for stills and character references. Narrative dialogue shots and action shots genuinely want different models. Having an agent that can see the whole storyboard helps route each shot instead of defaulting everything to whichever tab is open.

4. Knowing the cost before you generate.
Generation on the canvas shows the confirmed credit cost before anything runs, and credits are returned if a generation fails. With a BYOK connection, your model provider bills you directly at API rates and DramaCanvas charges no markup on model calls and deducts no platform generation credits — you only pay the workspace service fee. If you've ever watched a chat-based tool burn a subscription on failed generations, that transparency is the feature.

What it is not (yet)

• It is not a replacement for taste. The agent can structure, route and generate; shot selection and pacing are still yours.
• Manual work stays free — writing scripts and editing storyboards by hand costs nothing. AI generation is what consumes credits, and MCP-driven generation follows the same rules as clicking the button yourself: costs are confirmed per operation, there is no separate "agent fee."
• Your assets can be saved to a local folder you authorize, and the canvas can be exported as a ZIP. The platform does not promise cloud storage, and I'd rather say that plainly than imply it.

Why MCP for a filmmaking tool?

Because production is quietly becoming an agentic workflow whether the tools admit it or not. Directors already delegate structure to assistants; the assistant is now partly software. A canvas gives that software something a chat thread never can: a stable, spatial source of truth about the whole film — every beat, reference and clip in relation to everything else.

If you're building AI short dramas, MVs or commercials and want to try it: the canvas is live at dramacanva.com, planning is free, and the MCP config above is the whole integration. Break things, and tell me what the workflow gets wrong — that feedback is literally what the next iteration is built from.