Can I create, update, and delete content items in any collection?

Yes! Use `create_item` with a collection name and JSON payload to add new items. Use `update_item` with the collection, item ID, and updated fields to modify existing items. Use `delete_item` to remove items. All operations respect the permissions assigned to your Static Token's user role.

How does Directus authentication work with a Static Token?

Directus uses a non-expiring Static Token associated with a specific user account. Generate it from your **User Profile** in the Data Studio. The token is sent as a `Bearer` token in the Authorization header. Its permissions match the role assigned to that user — use an admin role for full access or a restricted role for read-only operations.

Can I audit what changes have been made to my database?

Yes. The `list_activity` tool retrieves the audit log of recent database operations, showing who made changes, which collections were affected, timestamps, and the type of operation (create, update, delete). Combine with `list_users` and `list_roles` for full accountability tracking.

INSTANT PLUG AND PLAY

Directus MCP Server for Pydantic AIGive Pydantic AI instant access to 16 tools to Check Directus Status, Create Item, Delete Item, and more

Name: Directus
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 16 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Directus through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Use with Your AI Agent

Ask AI about this App Connector for Pydantic AI

Open in ChatGPT Open in Claude Open in Perplexity

The Directus app connector for Pydantic AI is a standout in the Loved By Devs category — giving your AI agent 16 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Directus "
            "(16 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Directus?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Directus MCP Server

Connect your Directus instance to any AI agent and manage your content database through natural conversation.

Pydantic AI validates every Directus tool response against typed schemas, catching data inconsistencies at build time. Connect 16 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Collection Management — List all data collections with field counts and inspect individual collection schemas
Content CRUD — Create, read, update, and delete items in any collection using JSON payloads
Search & Query — Search items within collections by keyword to find specific content quickly
Schema Inspection — List all fields and their data types for any collection to understand your data model
File Management — Browse uploaded files and retrieve metadata for specific assets
User & Role Management — List all users with roles and status, view role configurations, and check your own profile
Audit Trail — Access the activity log of recent database operations for compliance and debugging

The Directus MCP Server exposes 16 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 16 Directus tools available for Pydantic AI

When Pydantic AI connects to Directus through Vinkius, your AI agent gets direct access to every tool listed below — spanning sql-database, graphql, rest-api, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_directus_status

Verify connectivity

create_item

Create an item

delete_item

Delete an item

get_collection

Get collection details

get_file

Get file details

get_item

Get item details

get_me

Get current user

list_activity

List recent activity

list_collections

List collections

list_fields

List fields

list_files

List files

list_items

List items

list_roles

List roles

list_users

List users

search_items

Search items

update_item

Update an item

Connect Directus to Pydantic AI via MCP

Follow these steps to wire Directus into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 16 tools from Directus with type-safe schemas

Why Use Pydantic AI with the Directus MCP Server

Pydantic AI provides unique advantages when paired with Directus through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Directus integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Directus connection logic from agent behavior for testable, maintainable code

Directus + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Directus MCP Server delivers measurable value.

Type-safe data pipelines: query Directus with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Directus tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Directus and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Directus responses and write comprehensive agent tests

Example Prompts for Directus in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Directus immediately.

"Show me all collections in my Directus instance and the fields for the 'articles' collection."

"Create a new article titled 'AI in Healthcare 2025' with status 'draft' and search for existing articles about AI."

"Show me the recent activity log and list all users with their roles."

Troubleshooting Directus MCP Server with Pydantic AI

Common issues when connecting Directus to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Directus + Pydantic AI FAQ

Common questions about integrating Directus MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Directus MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.