How to Use the BoxLock MCP in Pydantic AI

Q: Can Pydantic AI validate BoxLock barcode lists?

Yes, the tool response for listbarcodes is parsed into a validated model. Your agent only sees data that conforms to your strict definitions.

Build type-safe security workflows by pairing BoxLock with Pydantic AI for reliable, validated hardware control.

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Connect BoxLock MCP to Pydantic AI

Create your Vinkius account to connect BoxLock 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 BoxLock with Pydantic AI

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Validated Tool Execution in Pydantic AI

Your agent uses `press_to_open` with strict schema enforcement. Any malformed request is caught immediately by the Pydantic model. This prevents runtime crashes when sending commands to your hardware. You get a guarantee that the data payload matches expected formats every time.

Type-Safe Activity Tracking for Pydantic AI

Call `list_activities` to receive a structured response that maps perfectly to your Python types. Your agent processes these logs without worrying about hidden fields. It eliminates the risk of silent data corruption during parsing. Your logic stays clean because the data structure is validated at the boundary.

Hardware Discovery with Pydantic AI

Retrieve your lock inventory using `list_locks` and ensure the output matches your expected schema. The agent flags any unexpected response structure instantly. You build robust control loops that fail loudly rather than ignoring bad data. It provides the stability required for production deployments.

Setup guide

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

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

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

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Common questions about BoxLock MCP in Pydantic AI

Every MCP response is checked against a Pydantic model. If the server returns bad data, your agent stops before executing a faulty command.

Yes, the tool response for `list_barcodes` is parsed into a validated model. Your agent only sees data that conforms to your strict definitions.

You use the MCPToolset class to link the server URL. The framework handles the transport and ensures all communication remains type-safe.

It supports SSE transports for real-time data flow. Your agent receives updates as they arrive, keeping your local state synchronized.

By forcing response validation against a defined schema, your agent cannot hallucinate field names or values. You only work with verified user data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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