How to Use the FusionSignage MCP in Pydantic AI

Q: How do I install the FusionSignage MCP integration for Pydantic AI?

Run pip install pydantic-ai-slimmcp. Use the MCPToolset class with your HTTP endpoint and pass it to your agent's toolsets list.

Q: Can my Pydantic AI agent group screens together?

It calls listgroups to retrieve your existing configurations. It then validates the group IDs before assigning any new playlists.

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Connect FusionSignage MCP to Pydantic AI

Create your Vinkius account to connect FusionSignage 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 FusionSignage with Pydantic AI

Ask AI about this MCP

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Claude

Perplexity

Strict hardware validation

The `get_screen` and `get_playlist` tools pull your hardware configurations into strict Pydantic models. This MCP setup lets you define exactly what a valid screen response looks like. If the API returns a missing ID or malformed data, Pydantic AI throws a validation error immediately. Your agent stops before it hallucinates a nonexistent display.

Type-safe MCP Server updates

The `update_playlist` and `update_screen` tools modify your active network. The agent constructs the exact payload required by the endpoints. This FusionSignage MCP Server integration guarantees correctness. You pass the MCPToolset to your agent, and it enforces strict type checks on every single media update.

Model-agnostic execution

The `delete_playlist` and `delete_media` tools handle your cleanup routines. The agent removes outdated content without accidentally wiping your active campaigns. You write the execution logic once. Since the framework is model-agnostic, you swap between local models and heavy commercial LLMs without rewriting your tool definitions.

Setup guide

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

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

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

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Common questions about FusionSignage MCP in Pydantic AI

Run pip install pydantic-ai-slim[mcp]. Use the MCPToolset class with your HTTP endpoint and pass it to your agent's toolsets list.

The framework fails loudly. A validation error triggers instantly, preventing the agent from acting on corrupted or missing fields.

Yes. The MCPToolset implementation handles both Streamable HTTP and SSE connections. The old HTTP server class is deprecated.

It calls `list_groups` to retrieve your existing configurations. It then validates the group IDs before assigning any new playlists.

The server handles scheduling rules, playlist assignments, and media IDs. Vinkius manages the authentication layer, requiring only a single endpoint token while keeping your credentials isolated from the client logic.

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