How to Use the BoxyHQ (Enterprise SSO) MCP in Pydantic AI

Enforce strict schema validation for BoxyHQ (Enterprise SSO) tools within Pydantic AI.

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Connect BoxyHQ (Enterprise SSO) MCP to Pydantic AI

Create your Vinkius account to connect BoxyHQ (Enterprise SSO) 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 BoxyHQ (Enterprise SSO) with Pydantic AI

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Type-safe directory sync with Pydantic AI

Pydantic AI validates every response from `get_directory_users` against your defined models. If the schema shifts, the agent stops before processing bad data. This keeps your identity pipeline clean and prevents silent failures when directory formats change.

Create connections using Pydantic AI

The `add_connection` tool returns clear results that Pydantic AI parses into Python objects. You get full type safety for every field in your SAML configuration. It turns raw API responses into reliable data structures for your application logic.

Update SSO records with Pydantic AI

Use `update_connection` to modify your existing setup. Pydantic AI ensures the parameters you send match the exact requirements of the SSO server. You avoid common configuration errors because the framework validates your inputs before the request ever leaves your system.

Setup guide

Set up BoxyHQ (Enterprise SSO) 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": {
        "boxyhq-enterprise-sso-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent BoxyHQ (Enterprise SSO) transactions")
print(result.output)

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Common questions about BoxyHQ (Enterprise SSO) MCP in Pydantic AI

It provides runtime validation that stops your agent if it receives unexpected SSO data. You get a hard error instead of buggy behavior.

Use the slim version with MCP support. It keeps your dependency footprint small while giving you full access to the identity tools.

Yes, the MCP server maps directly to the toolset interface. Pydantic AI treats these tools like any other function, but with stricter validation.

It's an external server, so performance depends on your network. The validation overhead is negligible compared to the reliability you gain.

The server uses a zero-trust architecture. Your directory credentials never touch the model directly; they are handled by the server's internal logic and only exposed as validated tool results.

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