Content MCP Server

One asset, every platform: repurpose maps, platform specs, and the film-once-cut-many workflow. That is what the content mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

Creators burn out making NEW content daily. The leverage is making ONE strong thing and adapting it correctly for each platform — not reposting the identical file (which the algorithm and the audience both punish). This MCP maps any source asset to every format and gives the exact adaptation rules.

The tools it exposes

The server publishes 6 tools. What each one is for:

• get_repurpose_map — For a source (long video, podcast, blog, single short), every format it becomes + how to adapt it
• get_platform_specs — Aspect, length, caption style, hashtags, hook rule per platform (TikTok, Reels, Shorts, carousel, X thread, LinkedIn, newsletter)
• adapt_for_platform — The adaptation rules to reshape content for one platform, and what NOT to do
• extract_atomic_content — The 6 atomic pieces to pull from one asset (pull quotes, clips, stats, steps, story beats, questions)
• get_repurpose_workflow — The film-once-cut-many batch workflow, step by step
• get_full_pack — Everything in one payload

Getting it running

content-repurposing-mcp on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.

How it compares

This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Content's toolset — get_repurpose_map, get_platform_specs, adapt_for_platform and 3 more — is a fair guide to whether it matches your workflow. It is maintained by closermethod; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Things to watch

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.