How to Use the Mod.io MCP in Pydantic AI

Enforce strict types for your mod management logic using Pydantic AI.

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Connect Mod.io MCP to Pydantic AI

Create your Vinkius account to connect Mod.io 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 Mod.io with Pydantic AI

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Strict type-checking with Pydantic AI

Every response from `get_mod` or `get_games` is validated against your Pydantic models. If the schema shifts, the agent stops immediately. This prevents silent failures in your code. You get full runtime validation for every piece of data moving through the server.

Secure mod management for Pydantic AI

Use `edit_mod` or `delete_mod` with full confidence. The framework validates the inputs before the request ever hits the network. It keeps your agent logic clean. Your code handles defined objects rather than raw, unreliable JSON blobs.

Automate user interactions in Pydantic AI

Retrieve user data via `get_me` and map it to your internal user classes. It makes managing `get_my_ratings` simple and type-safe. Your agent logic becomes predictable. You define the structure, and the tools fill in the blanks with guaranteed data types.

Setup guide

Set up Mod.io 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": {
        "modio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Mod.io MCP in Pydantic AI

Define your Pydantic models to match the tool outputs. The framework automatically validates the MCP server responses against these models.

Yes. Validation errors will trigger if the server returns unexpected data due to auth issues, allowing your agent to handle the failure gracefully.

It is. The integration supports async transport, fitting naturally into your non-blocking agent workflows.

The agent raises a validation error immediately. This stops the process before any bad data propagates through your system.

Vinkius ensures secure transport. Since your agent uses strictly defined types, sensitive data like wallet balances from `get_my_wallets` is handled predictably and securely.

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