Directus MCP Server

The Directus MCP Server bridges the gap between AI assistants and a Directus content management system by exposing the full range of Directus API operations through the Model Context Protocol. Instead of writing custom integrations for each AI workflow, developers can now call Directus resources directly from Claude or Cursor as if they were native tools. This eliminates the need for repetitive boilerplate code, centralizes authentication handling, and guarantees that all interactions respect Directus’ permission model.

At its core, the server implements a set of tools that mirror standard Directus endpoints. Developers can fetch collections, query items by ID or filter, create and update records, delete entries, and manage file uploads. In addition to CRUD operations, the server exposes schema information—such as collection definitions and field metadata—and user‑related actions like login and permission checks. By providing these capabilities through MCP, the server turns Directus into a first‑class data source that AI assistants can query and manipulate on demand.

Key features include:

• Unified authentication: Accept either a static access token or an email/password pair, automatically handling session creation and token refresh.
• Rich schema awareness: Retrieve collection schemas, field definitions, and relationships so that AI tools can generate context‑aware prompts or validate data structures before performing actions.
• File management: Upload and list files, enabling AI workflows that require media handling—such as generating image captions or embedding documents.
• User and permission tooling: Log in, fetch user lists, and respect Directus’ granular permissions, ensuring that AI actions are constrained by the same rules as manual users.

Real‑world scenarios abound. A content editor using Claude can ask the assistant to “list all blog posts tagged ‘AI’ and update their status to published,” and the MCP server will translate that into a direct Directus query. A data scientist can prompt Claude to “fetch the latest 50 sales records and compute a moving average,” with the assistant retrieving data via MCP before performing calculations. In continuous‑integration pipelines, a CI tool can trigger the server to seed test data into Directus or clean up after tests, all orchestrated through MCP commands.

Integration is straightforward: add the server’s configuration to your AI client (Cursor, Claude Desktop, or any MCP‑compatible editor), and the tools become available in the assistant’s toolbox. Because MCP standardizes tool invocation, developers can compose complex sequences—such as retrieving a record, modifying it, and uploading an associated file—in a single prompt. This composability reduces friction and accelerates prototyping, making the Directus MCP Server a powerful addition to any AI‑first development stack.