Prism Videos MCP — Railway

This repository is a Railway-ready MCP server written in Python.

Architecture

Claude → MCP (Railway) → Prism Videos API

The server exposes a Streamable HTTP MCP endpoint at:

/mcp

and a health endpoint at:

/health

Related MCP server: golpo-mcp

Important Prism API limitation

The official Prism API documentation currently describes:

• character management

• template browsing/details

• polling generation status

• downloading completed generations

It does not currently document a public API endpoint for starting a brand-new video generation from a prompt.

Therefore this repository deliberately does NOT invent a fake generation endpoint.

prism_generate_video only activates when PRISM_GENERATE_ENDPOINT is explicitly configured.

Do not guess an endpoint such as /generate or /video/generations.

Railway deployment

1. Push this repository to GitHub.

2. In Railway choose New → GitHub Repository.

3. Select this repository.

4. Railway will detect the root Dockerfile.

5. Add the following Railway Variables:

PRISM_API_KEY=your_real_prism_api_key
PRISM_BASE_URL=https://prismvideos.com/api
PRISM_GENERATE_ENDPOINT=
PRISM_TIMEOUT_SECONDS=120

Do NOT commit the real Prism API key to GitHub.

Railway stores service variables separately from the repository.

6. Deploy.

7. Generate a public Railway domain.

8. Your MCP endpoint will be:

https://YOUR-RAILWAY-DOMAIN/mcp

Health check:

https://YOUR-RAILWAY-DOMAIN/health

Local test

Python 3.10+ is required by the current MCP Python SDK.

Install:

pip install -r requirements.txt

Set environment variables from .env.

Run:

uvicorn server:app --host 127.0.0.1 --port 8000

MCP endpoint:

http://127.0.0.1:8000/mcp

What we still need for full Prism automation

To make Claude create six scenes automatically and return a finished ~30-second Short, we need an officially supported Prism generation API call.

Once Prism provides that endpoint/schema, the intended pipeline is:

1. Claude creates the six scene prompts.

2. MCP calls Prism for each scene.

3. MCP polls each generation.

4. MCP downloads each finished clip.

5. FFmpeg joins the six clips.

6. MCP returns the final video URL/file reference.

This repository already contains the MCP/HTTP/Railway foundation for that workflow.

Security note

The initial deployment disables MCP DNS-rebinding protection so the automatically generated Railway hostname works immediately.

After the Railway domain is known, the TransportSecuritySettings in server.py should be changed to an exact hostname allowlist.

For a public production MCP server, add proper MCP authorization/OAuth before exposing it broadly.