Native MCP support transforms content management into an AI-collaborative workflow, making teams more capable and productive together
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BROOKLYN, New York – October 28, 2025 – Directus, the data platform with over 40 million downloads and 33,000 GitHub stars, today announced the general availability of its native Model Context Protocol (MCP).
After a successful beta period, this launch positions Directus as the industry's first truly collaborative CMS, bringing together marketers, developers, and AI to eliminate the bottlenecks that have plagued teams for years.
Marketing needs a landing page. They submit a ticket. It goes into the backlog. Three weeks later, a developer carves out two hours between feature development work. The page goes live, but now marketing wants to set-up a new A/B test. Another ticket. Another wait.
It's exhausting for everyone involved.
Directus MCP finally puts an end to this. It doesn't cut developers out of the loop. Instead, it lets AI handle the translation layer between "we need this content" and "here's how it needs to be structured in the database".
A content editor can say "import this blog post from Google Docs into my articles collection," and the AI understands both the creative intent and the technical schema. It creates properly structured entries with correct field types, relationships, and validation. Developers maintain control and visibility without being the middleman for every content update.
"We're not building AI features to replace people. We're building it to make collaboration effortless," said Rijk van Zanten, CTO at Directus.
"The real breakthrough isn't that AI can generate content. It's that AI can finally speak both languages fluently: marketer and developer. That's what unlocks real collaboration."
Using Anthropic’s Claude with Directus MCP to quickly stage content, like blog posts and landing pages.
Here's the thing about MCP: it's not about automating content creation at scale. Plenty of tools will happily churn out thousands of mediocre blog posts for you. That's not interesting.
What's interesting is how it dissolves the barriers between teams. A content manager can describe what they need in plain language while the AI ensures it matches the technical requirements developers set up.
Marketing can make bulk changes to structured data without waiting for a developer to write a script, but within the guardrails and validation rules developers established.
When a developer builds a new data model, non-technical teams can immediately start using it through natural language without needing documentation or training.