AI · MCP Server
Agility CMS exposes content operations to AI agents through a Model Context Protocol server. Agents create, model, publish, and manage content under the same permissions and workflows as any user.
claude mcp add --transport http "Agility-CMS" https://mcp.agilitycms.com/api/mcpYou stay in control. Agents operate inside your permissions, your workflows, and your approval steps. High-stakes operations use confirmation gates, so a human approves before anything goes live.
There are two MCP servers, and they do different jobs.
Connect both. An agent that can look up how a feature actually works before it uses it makes noticeably fewer mistakes with the management server.
The tools map onto what you'd do in the app yourself:
The connection uses OAuth and the agent acts as you. It can't reach an instance you can't reach, and it can't do anything your role forbids. Workflow still applies too. If a content type needs approval before it publishes, the agent hits that gate like anyone else.
Think of it as a fast, literal colleague with access to your instance. It's good at work that's tedious rather than delicate: finding things, filling gaps, applying the same change across a lot of items.
Where it earns its keep:
One thing to hold onto: saving isn't publishing. Anything an agent writes lands in Staging as a new version, and your live site doesn't move. Publishing is a separate step you take deliberately. Use that gap, and read what it did before you push it live.
The management server is most useful for the work around the code: standing up an instance, keeping models and components in step, reshaping content that already exists.
Describing a model in prose and letting the agent build it is faster than clicking through the model editor, and you can read back exactly what it made. Ask it for the model, the container, and a dozen sample items in one go, so there's something real to build against straight away.
A model change is live the moment it saves. Add a field without shipping the component change and the site degrades quietly. An agent that can see both the model and the component that renders it can do the two together, which is where most of that risk sits.
Agents are only as good as their context. A file in your repo holding your instance GUIDs, container reference names, component conventions and the gotchas your team has hit will do more for the output than any amount of prompting.
An empty instance has no legacy to work around, so it's the easiest place to start. A sequence that works:
Order matters here. Creating the models and the code that consumes them in the same session is what keeps the two from drifting apart.
Migrations tend to be too big to do by hand and too specific to be worth scripting. That gap is where this works best.
Typical jobs:
Author text field becomes a linked Author item across several hundred posts, deduplicated on the way through.Two rules make this safe. Work in batches: ten items, stop, look at the result, then let it do the other four hundred. And make it read before it writes, because an update sends the whole item back. A field the agent didn't read is a field it can blank.
Do a dry run first. Have the agent tell you what it's about to change and do the first few items only, before it takes on the rest. Staging gives you a version to compare against, but checking ten items is a lot easier than unpicking four hundred.
Locales are first-class in Agility, so translating through an agent is a content operation rather than an export-and-reimport trip. It reads the source locale, translates, and writes into the target locale on the same instance.
Why that beats pasting into a translation tool:
Check which locales the instance actually has before you start. The agent can read that rather than assume it.
Worth knowing before you lean on any of this:
Most of these only catch you once.
Connect an agent, then go deeper — from the management MCP server to AI-assisted app building.