Prepublish MCP README

prepublish-mcp

Audit a YouTube script before you record it, from inside your AI client.

Prepublish is a remote MCP server. It reads a draft that does not exist as a video yet and returns hook, structure and pacing scores, the passages most likely to lose viewers, an inauthentic-content check, a YouTube policy pre-flight that cites YouTube's own published pages, and a words-to-runtime calculator built on measured speaking rates.

Every other YouTube MCP server fetches the transcript of a video that is already published. This one reads the script you have not filmed.

Free, anonymous, no API key, no account.

Install

Claude Code, one command:

Terminal

claude mcp add --transport http prepublish https://mcp.prepublish.ai

Cursor, VS Code, Windsurf, Claude Code project scope, or anything that reads an mcpServers object:

config.json

{
  "mcpServers": {
    "prepublish": {
      "type": "http",
      "url": "https://mcp.prepublish.ai"
    }
  }
}

Claude Desktop: add a custom connector under Customize, then Connectors, and paste https://mcp.prepublish.ai.

Codex CLI, ~/.codex/config.toml:

toml

[mcp_servers.prepublish]
url = "https://mcp.prepublish.ai"

Clients that can only launch a command use the stdio bridge in this repository. It needs Node 20 or newer and forwards to the same endpoint:

config.json

{
  "mcpServers": {
    "prepublish": {
      "command": "npx",
      "args": ["-y", "prepublish-mcp"]
    }
  }
}

Agents installing this on a user's behalf should read llms-install.md.

Check it worked

Ask for a runtime estimate: "Use prepublish to convert 1500 words into a runtime range." script_runtime is local arithmetic, never rate limited, and returns three estimates. If that answers, the connection is good.

Tools

Tool	Cost	What it returns
`audit_script`	AI-backed	Full audit of a finished draft: hook, structure and pacing scores, an attention-risk map naming the passages most likely to lose viewers, and a rewrite. Returns the analysis and its id
`get_audit`	free	Collect an earlier audit by `analysis_id`
`audit_hook`	AI-backed	Per-sentence attention pull across the opening, curiosity gap, payoff distance, a grade, and rewritten alternatives
`check_authenticity`	AI-backed	Reused, templated or mass-produced content risk, with the quotes that fired each signal
`policy_preflight`	AI-backed	Which YouTube policy families a script touches, each citing YouTube's own page
`script_runtime`	free, local	Words to runtime and runtime to a word budget, at 160, 181 and 201 words per minute measured across 349 videos

audit_script asks for an email address, because the full audit is released by email. The other five do not.

What it does not do

Every AI-backed response carries the same notice, and it is worth stating here too. These checks are text-only. They map relative attention risk inside an unrecorded script. They do not measure or predict the retention a published video will get, and no output here is a forecast of views, watch time or revenue.

Nothing fetches a video, a transcript or a channel. Every tool reads text you pass it.

Limits

The free tier is published live at GET https://mcp.prepublish.ai, which returns a machine-readable server card with the current day's usage.

Limit	Default
AI-backed calls per UTC day, across the whole endpoint	100
AI-backed calls per caller per 10 minutes	6

script_runtime is local arithmetic and never counts against either.

A bearer token in PREPUBLISH_TOKEN raises the limits without changing the tool list.

When the daily cap is reached the tool returns an error that tells the model not to retry and names the web alternative for that day. Failures return the next action rather than a stack trace.

Transport and protocol

Streamable HTTP, stateless. Supported revisions: 2025-11-25, 2025-06-18, 2025-03-26, 2024-11-05. A client asking for a supported revision gets it back; anything else negotiates to the newest one implemented, and the negotiated revision is reported identically in the response header and in the initialize result.

The endpoint validates the Origin header. Requests without one, which is every non-browser client, are always served. A browser origin that is not prepublish.ai is refused with 403, as the transport specification requires. An unsupported MCP-Protocol-Version header is a 400.

Aliases: https://prepublish.ai/mcp and https://mcp.prepublish.ai/mcp serve the same handler.

Development

The server itself lives in the Prepublish web application, not in this repository. What is here is the stdio bridge and the conformance suite that holds the hosted endpoint to the specification.

Terminal

npm install
npm run build
MCP_URL=https://mcp.prepublish.ai npm test

The suite drives the endpoint with the official MCP SDK client over Streamable HTTP, so the wire format is checked against the reference implementation rather than against our own assumptions. It covers the handshake, tool discovery, schema shape, both directions of script_runtime, unknown-tool errors, the server card, batching rejection, notification handling, protocol negotiation in both directions, Origin validation, protocol version validation, and the stdio bridge round trip.

One AI-backed test is skipped unless MCP_TEST_BILLABLE=1, because a real call costs money and writes a row.

PREPUBLISH_MCP_URL overrides the upstream endpoint for the bridge. The bridge adds and hides nothing: a test asserts its tool list equals the hosted one, so adding a tool on the server needs no release here.

Registry

Published to the official MCP registry as ai.prepublish/script-audit, a remote-only entry under the DNS-verified ai.prepublish namespace. See server.json.

License

MIT. See LICENSE.