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Contentrain / MCP Servers · Official registry

ai

Repo-native content governance for AI agents. Extract, review, and deliver UI text, docs, and structured content from Git.

  • 6 stars
  • 0 forks
  • 3 open issues
  • Language: TypeScript
  • License: MIT
  • updated

Install

remote
Terminal
claude mcp add --transport http ai 'https://studio.contentrain.io/api/mcp/v1/{project_id}/mcp'
.mcp.json (project scope)
{
  "mcpServers": {
    "ai": {
      "type": "http",
      "url": "https://studio.contentrain.io/api/mcp/v1/{project_id}/mcp"
    }
  }
}

Remote server, no local binary. If it asks for credentials, follow the provider's README. Replace the values in braces in the URL with your own.

  1. Run the command in your terminal (Claude Code), or add the URL as a connector (Claude Desktop) or in mcp.json (Cursor).
  2. Authorise access when the client asks.
  3. Restart the session: the server's tools show up automatically.
README

MCP Servers overview

Full README on GitHub

Contentrain AI

npm: @contentrain/mcp npm: contentrain npm: @contentrain/query Agent Skills Docs License: MIT

Website · Docs · Discord · Twitter · LinkedIn

Extract, govern, and ship structured content from your codebase.

Contentrain helps teams turn hardcoded UI text, docs, and structured content into a governed, reviewable content layer. Agents can extract, create, translate, and update content, while Contentrain enforces schema, Git review, and portable file output.

Agent extracts or updates content → Contentrain standardizes → Human reviews → Any platform consumes

Try it in 30 seconds

npx contentrain init        # create .contentrain/ workspace
npx contentrain serve       # open the local review UI

That's it. You now have a governed content workspace with models, validation, review branches, and a local UI — no account, no cloud, no proprietary content format.

Start here:

What Contentrain is for

  • Rescuing hardcoded strings from existing apps and turning them into structured, translatable content

  • Starting new projects with a real content layer instead of scattering copy across components

  • Serving the same content across web, docs, mobile, and backend systems from plain JSON and Markdown in Git

What it is not

  • Not an AI writing app

  • Not a database-first or dashboard-first CMS replacement for every team

  • Not a proprietary content runtime that locks your app to one platform

What it looks like

Before: Hardcoded strings scattered across your codebase — no structure, no translations, no review.

export default function Hero() {
  return (
    <section>
      <h1>Welcome to our platform</h1>
      <p>Start your free trial today</p>
      <button>Get Started</button>
    </section>
  )
}

After: Content lives in .contentrain/, typed and structured. Source files use i18n keys.

export default function Hero() {
  const t = useTranslations()
  return (
    <section>
      <h1>{t('hero.title')}</h1>
      <p>{t('hero.subtitle')}</p>
      <button>{t('hero.cta')}</button>
    </section>
  )
}
// .contentrain/content/marketing/hero/en.json
{
  "cta": "Get Started",
  "subtitle": "Start your free trial today",
  "title": "Welcome to our platform"
}

The normalize flow extracts strings, creates models, and patches your source files — all through reviewable git branches.

This is the strongest entry point into the product:

take the content chaos already in your codebase and turn it into a governed, reviewable content layer.

How it works

┌─────────────┐     ┌──────────────────┐     ┌──────────────┐
│  AI Agent    │────▶│  MCP (27 tools)  │────▶│ .contentrain/│
│  (decides)   │     │  (enforces)      │     │ (stores)     │
└─────────────┘     └──────────────────┘     └──────┬───────┘
                                                     │
                    ┌──────────────────┐              │
                    │  Review UI / Git │◀─────────────┘
                    │  (human approves)│
                    └──────────────────┘
  • Agent decides what content should exist and where it should come from

  • Contentrain enforces schemas, validation, canonical serialization, and git workflow

  • Human reviews through branches, PRs, or the local Serve UI

  • Output is plain JSON + Markdown that any language or framework can consume

4 content kinds

KindWhat it storesStorageExample
CollectionMultiple typed entriesJSON object-mapBlog posts, products, team
SingletonSingle entry per localeJSON objectHero section, site config
DocumentMarkdown + frontmatter.md filesDocs, articles, changelog
DictionaryFlat key-value stringsJSON flat mapi18n translations, UI labels

27 field types (string, email, url, image, relation, array, object, markdown, ...) with built-in validation.

Use your content anywhere

Content is plain JSON and Markdown. Any language reads it directly.

For TypeScript projects, generate a typed SDK:

npx contentrain generate
import { query, singleton, dictionary, document } from '#contentrain'

const hero    = singleton('hero').locale('en').get()
const posts   = query('blog-post').locale('en').include('author').all()
const labels  = dictionary('ui-labels').locale('tr').get('auth.login')
const article = document('docs').locale('en').bySlug('getting-started')

Works with Nuxt, Next.js, Astro, SvelteKit, Vue, React, Node, Go, Python, Swift, Flutter, and 20+ stacks.

Why teams use it

  • Git-native — every write goes through worktree isolation + review branches

  • Normalize flow — scan codebase for hardcoded strings → extract → create i18n-ready content → patch source files

  • MCP engine — 27 tools (22 core + 5 media) over stdio or HTTP transport, works with Claude Code, Cursor, Windsurf, or any MCP client

  • Provider-agnostic engine — the same tool surface runs over a local worktree, GitHub, or GitLab (self-hosted included) with zero tool-code changes. HTTP transport available for remote drivers such as Studio.

  • Canonical serialization — sorted keys, deterministic output, clean git diffs, conflict-free parallel edits

  • Agent rules & skills — behavioral policies and step-by-step workflows ship as npm packages

  • Serve UI — local web dashboard for browsing models, content, validation, and normalize status

  • Framework-agnostic — MCP doesn't know your framework. Agent + skills handle stack-specific logic

Agent Skills

This repo ships 16 Agent Skills — reusable workflow procedures that any AI coding agent can load on demand.

Install all skills to your agent:

npx skills add Contentrain/ai/packages/skills

Or install a specific skill:

npx skills add Contentrain/ai/packages/skills --skill contentrain-normalize

Skills work with Claude Code, Cursor, Windsurf, GitHub Copilot, OpenAI Codex, Gemini CLI, and 40+ other agents.

See AGENTS.md for the full skill catalog and agent guidance.

Packages

PackagenpmRole
@contentrain/mcpnpm27 MCP tools + stdio / HTTP transport + Local / GitHub / GitLab providers
contentrainnpmCLI + Serve UI + MCP stdio entrypoint
@contentrain/querynpmGenerated TypeScript query SDK
@contentrain/typesnpmShared type definitions + constants
@contentrain/rulesnpmAgent quality rules for IDE integration
@contentrain/skillsnpmWorkflow procedures + framework guides
@contentrain/wp-importnpmWordPress WXR / REST → RawIR → .contentrain store
@contentrain/emitter-astronpmProjectIR → a complete Astro project
@contentrain/verifynpmSEO, indexing, link and asset gates for a built site
@contentrain/astro-kitnpmCopy-in Astro components + catalog + builder mapping tables
@contentrain/decidenpmTyped decisions — rule first, then Jev, then Claude Haiku — cached, budgeted, audited

Starter Templates

Production-ready templates with Contentrain content models, generated SDK client, and framework-specific patterns:

TemplateFrameworkUse Case
astro-blogAstroBlog / editorial
astro-landingAstroLanding page
Topics
ai-agentsclaude-codecontent-governancecontentraincursordeveloper-toolsgiti18nmcpmcp-servermodel-context-protocolsdktypescriptwindsurf
Frequently asked

What people ask about ai

What is Contentrain/ai?

Contentrain/ai is mcp servers for the Claude AI ecosystem. Repo-native content governance for AI agents. Extract, review, and deliver UI text, docs, and structured content from Git. It has 6 GitHub stars and its last recorded update is dated 2026-10-22.

How do I install ai?

You can install ai by cloning the repository (https://github.com/Contentrain/ai) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is Contentrain/ai safe to use?

Our security agent has analyzed Contentrain/ai and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains Contentrain/ai?

Contentrain/ai is maintained by Contentrain. The last recorded GitHub activity is dated 2026-10-22, with 3 open issues.

Are there alternatives to ai?

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.