MCP Storyblok Server Overview

The MCP Storyblok Server bridges the gap between AI assistants and the powerful content management capabilities of Storyblok. By exposing a rich set of tools that mirror every major feature of the CMS—stories, assets, components, tags, releases, and spaces—the server allows an AI to act as a first‑class editor, publisher, or content discoverer without ever leaving the conversational interface. This is especially valuable for developers building AI‑augmented workflows, where content creation and publishing need to happen in real time or be triggered by external events.

At its core, the server implements a clean, modular architecture. Each feature set lives in its own file under , making it trivial to add or remove capabilities without touching unrelated code. The tool implementations use a shared API helper layer that handles authentication, request formatting, and error handling, ensuring consistent behavior across all endpoints. The server also leverages TypeScript’s type system to provide strong contracts for every request and response, reducing runtime surprises and improving IDE support for developers who integrate the MCP into their own codebases.

Key capabilities include:

• Story Lifecycle Management – Create, update, delete, publish, unpublish, and version stories. This lets an AI assistant draft content, push revisions to reviewers, or schedule a final publish date.
• Asset Handling – Upload assets through an init/complete workflow, organize them into folders, and retrieve metadata. AI can embed images or media directly in stories by orchestrating the upload pipeline.
• Component Schema Control – Define and update reusable block schemas, enabling dynamic content modeling that adapts to evolving business needs.
• Tagging and Release Orchestration – Tag content for categorization, then bundle stories into releases that can be scheduled or published in bulk.
• Advanced Search and Discovery – Perform filtered queries across stories, assets, or components, allowing an AI to surface relevant content for user requests or analytics.

Developers can integrate these tools into any MCP‑compatible AI workflow. For example, a chatbot could prompt a user for headline text, generate a draft story via , attach an AI‑generated image using the asset upload tools, and then schedule a release with . Because every tool is defined in the MCP schema, the AI can introspect available actions and dynamically compose sequences of operations without hard‑coding API endpoints.

What sets this server apart is its comprehensive coverage of Storyblok’s feature set combined with a developer‑friendly, type‑safe implementation. The modular design means that teams can cherry‑pick the tools they need—such as only exposing story and asset operations for a content‑creation bot—while still benefiting from the same underlying authentication and error handling infrastructure. In practice, this translates to faster prototyping of AI‑powered content pipelines, reduced maintenance overhead, and a smoother developer experience when extending or customizing the server for specific use cases.