How to Use the Directus MCP in Pydantic AI

Q: How do I verify the connection status?

You can have your agent run checkdirectusstatus at startup. This verifies that your API credentials and endpoint are working before executing any database queries.

Q: How are my Directus files protected during validation?

File metadata fetched via getfile or listfiles is validated locally inside your application memory. Vinkius secures the transport layer using ephemeral sandboxes, meaning no file data is cached or stored on our servers.

Run type-safe database operations in Pydantic AI with strict runtime validation for Directus.

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Connect Directus MCP to Pydantic AI

Create your Vinkius account to connect Directus to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Directus with Pydantic AI

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Strict Runtime Validation for Directus

Pydantic AI enforces type safety on every database response, preventing your agent from processing malformed data. When the agent calls `get_item` or `list_items`, the returned JSON is validated against your Pydantic models at runtime. If a field type changes or a database column is missing, the framework fails loudly with a validation error. This prevents silent failures and ensures your application state remains consistent.

Safe Schema Mapping via MCP Server

This MCP Server allows Pydantic AI to dynamically map your database collections into validated Python classes. Your agent queries the schema using `list_collections` and `list_fields` to build accurate data structures on the fly. By verifying field definitions before executing writes like `create_item` or `update_item`, you eliminate runtime database errors caused by incorrect data types or missing required fields.

Type-Safe User and Role Auditing

Audit your database access securely using validated user management tools. The agent calls `list_users`, `list_roles`, and `get_me` to verify identities and roles against strict Pydantic schemas before granting access to sensitive data. This ensures that any permission check or user query is fully typed, eliminating the risk of security gaps caused by unvalidated API payloads.

Setup guide

Set up Directus MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "directus-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Directus tools.",
)

result = await agent.run("List recent Directus transactions")
print(result.output)

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Common questions about Directus MCP in Pydantic AI

Initialize the MCP toolset with your Vinkius HTTP endpoint. Pass the toolset directly to your `Agent` constructor to expose tools like `list_items` with strict type validation.

The framework immediately raises a validation error instead of passing bad data to the model. This keeps your application safe from hallucinated fields or corrupted database records.

Yes, your agent can validate write payloads against a Pydantic model before calling `create_item` or `update_item`. This ensures only clean, properly formatted data hits your database.

You can have your agent run `check_directus_status` at startup. This verifies that your API credentials and endpoint are working before executing any database queries.

File metadata fetched via `get_file` or `list_files` is validated locally inside your application memory. Vinkius secures the transport layer using ephemeral sandboxes, meaning no file data is cached or stored on our servers.

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