Give AI agents bounded content operations
Agents can create, update, translate, search, and validate content through deterministic tools instead of editing source strings directly.
$ contentrain serve
◇ 19 bounded tools available
contentrain_scan contentrain_apply
contentrain_validate contentrain_submit
contentrain_content_save contentrain_merge
# the agent can only do what the tools allow
Governance
AI content needs an operating boundary
If agents can freely edit copy, schemas, translations, and docs, quality depends on prompts alone. Contentrain gives agents tools, rules, validation, and review paths that define acceptable operations.
- MCP tool boundaries
- Shared rules and skills
- Validation before delivery
▸ "Add a pricing FAQ entry"
→ contentrain_content_save
model: faq locale: en
→ contentrain_validate
✓ Saved to branch cr/content/faq
# agent proposes · you approve in Git
Context
Make project context visible to the agent
The .contentrain project files describe models, context, vocabulary, content, and metadata in the repo. Agents can inspect the content system before they generate or modify product copy.
- Project context file
- Vocabulary and model definitions
- Content files readable in Git
# Agent operating rules
- Save content through MCP tools only
- Validate against the schema before submit
- Open a review branch per change
- Never edit generated files
# shared by every agent on the repo
Quality
Use rules for quality, not taste
The rules package covers content quality, SEO, i18n, accessibility, media, schema, security, normalize, and workflow expectations. That turns subjective review into repeatable checks.
- SEO title and description guidance
- Locale and schema validation expectations
- Security and MCP usage rules
Approval
Require human review for production changes
Content governance is not complete until humans can approve important changes. Studio branch review, diff views, roles, and branch health checks make that possible for AI-assisted content.
- Branch detail views
- Reviewer and editor paths
- Health checks before merge
$ contentrain diff
● Pending branches (3)
cr/content/marketing/hero +2 / -1
cr/content/blog/launch +5 / -0
cr/content/faq/pricing +1 / -0
✓ Approve in Git → merged to main
Lifecycle
Govern the whole content lifecycle
The same operating model can cover extraction, writing, translation, media, delivery, forms, webhooks, and external conversation APIs. That is why Contentrain is more than a prompt guideline.
- Normalize and translation workflows
- Studio media and delivery surfaces
- Conversation API for controlled external operations
Common questions
What is AI content governance?
It is the system of tools, rules, validation, permissions, and review workflows that controls how AI creates or changes product content.
Why is Git important for governance?
Git gives content changes history, diffs, branches, and review habits that engineering teams already trust.
Can governance start locally?
Yes. The MIT packages let a developer start with local MCP, rules, validate, normalize, and generated access before Studio is needed.
Next paths
Continue through the content system
Start local. Scale to Studio.
Build a governed content layer before content becomes product debt.
Developers can start with the MIT packages. Teams can move into Studio when review, roles, delivery, and licensing matter.