How to Use the Loomly MCP in Pydantic AI

Q: How do I set up Loomly with Pydantic AI?

Install the pydantic-ai-slim package and initialize the MCPToolset with your server URL. It handles the transport and type validation automatically.

Q: Can Pydantic AI handle Loomly media assets?

Yes. The listmediaassets tool is fully compatible. Pydantic models will validate the file list returned from your media library.

Use Pydantic AI for type-safe social media management with Loomly, ensuring every API interaction is validated at runtime.

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Connect Loomly MCP to Pydantic AI

Create your Vinkius account to connect Loomly 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 Loomly with Pydantic AI

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Validate Loomly posts with Pydantic AI

The `create_new_post` tool enforces strict field types. If your agent tries to send malformed data, Pydantic AI catches it before it hits the API. This prevents bad requests from reaching your calendar. You get immediate feedback if your agent's output doesn't match the expected schema.

List posts safely using Pydantic AI

Use `list_calendar_posts` to pull active content. Pydantic models verify the structure of every post returned by the server. This ensures your agent never works with corrupted or unexpected data. It is the safest way to maintain your social calendar state.

Audit Loomly interactions with Pydantic AI

The `list_post_interactions` tool returns structured engagement data. Pydantic AI validates the comment and reply objects as they arrive. You avoid silent failures common with raw API responses. If the data format changes, your agent crashes safely instead of hallucinating fields.

Setup guide

Set up Loomly 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": {
        "loomly-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Loomly MCP in Pydantic AI

Install the pydantic-ai-slim package and initialize the `MCPToolset` with your server URL. It handles the transport and type validation automatically.

It provides runtime type safety. Every response from the server is checked against a schema, ensuring your agent logic remains sound.

Yes. The `list_media_assets` tool is fully compatible. Pydantic models will validate the file list returned from your media library.

Your connection uses a single endpoint token managed by Vinkius. We ensure the connection is encrypted and isolated from other processes.

The server provides the structure for posts, calendars, and interactions. These are mapped to your models to prevent any runtime errors.

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