If you're tired of hardcoded strings scattered across your codebase, this gives Claude 17 MCP tools to extract, structure, and govern content through a local-first Git workflow. It normalizes existing UI text into typed models (collections, singletons, documents, dictionaries), enforces schema validation, and outputs plain JSON and Markdown that any stack can consume. The normalize flow scans your files, extracts strings, creates i18n-ready content, and patches source files with translation keys, all through reviewable branches. Works over stdio with a local worktree or HTTP with GitHub/GitLab providers. Ships with a local review UI and 15 Agent Skills for repeatable workflows. Strong fit if you want structured content governance without a proprietary CMS runtime.
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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
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:
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.
┌─────────────┐ ┌──────────────────┐ ┌──────────────┐
│ AI Agent │────▶│ MCP (19 tools) │────▶│ .contentrain/│
│ (decides) │ │ (enforces) │ │ (stores) │
└─────────────┘ └──────────────────┘ └──────┬───────┘
│
┌──────────────────┐ │
│ Review UI / Git │◀─────────────┘
│ (human approves)│
└──────────────────┘
| Kind | What it stores | Storage | Example |
|---|---|---|---|
| Collection | Multiple typed entries | JSON object-map | Blog posts, products, team |
| Singleton | Single entry per locale | JSON object | Hero section, site config |
| Document | Markdown + frontmatter | .md files | Docs, articles, changelog |
| Dictionary | Flat key-value strings | JSON flat map | i18n translations, UI labels |
27 field types (string, email, url, image, relation, array, object, markdown, ...) with built-in validation.
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.
This repo ships 15 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.
| Package | npm | Role |
|---|---|---|
@contentrain/mcp | 19 MCP tools + stdio / HTTP transport + Local / GitHub / GitLab providers | |
contentrain | CLI + Serve UI + MCP stdio entrypoint | |
@contentrain/query | Generated TypeScript query SDK | |
@contentrain/types | Shared type definitions + constants | |
@contentrain/rules | Agent quality rules for IDE integration | |
@contentrain/skills | Workflow procedures + framework guides |
Production-ready templates with Contentrain content models, generated SDK client, and framework-specific patterns:
| Template | Framework | Use Case |
|---|---|---|
| astro-blog | Astro | Blog / editorial |
| astro-landing | Astro | Landing page |
| next-commerce | Next.js | E-commerce storytelling |
| next-multi-surface-saas | Next.js | Marketing + app + docs unified |
| next-saas-dashboard | Next.js | SaaS dashboard UI copy |
| next-white-label-portal | Next.js | White-label / multi-tenant |
| nuxt-admin-console | Nuxt | Admin console / operations |
| nuxt-saas | Nuxt | SaaS marketing site |
| sveltekit-editorial | SvelteKit | Editorial / publication |
| vitepress-docs | VitePress | Documentation site |
Each template is a GitHub template repo — click "Use this template" to start.
npx contentrain init # initialize project
npx contentrain serve # local review UI (port 3333)
npx contentrain serve --stdio # MCP over stdio for IDE agents
npx contentrain validate # check content health
npx contentrain generate # generate typed SDK client
npx contentrain status # project overview
npx contentrain doctor # setup health check
npx contentrain studio login # authenticate with Studio
npx contentrain studio connect # connect repo to Studio project
pnpm install && pnpm build && pnpm test
See RELEASING.md for the versioning and publish workflow.
If Contentrain AI is useful to you, consider giving it a star — it helps others discover the project.
MIT