How to Use the CPSC (Consumer Product Safety Commission) MCP in Pydantic AI

Enforce strict safety data schemas in Pydantic AI with this CPSC (Consumer Product Safety Commission) MCP Server.

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Connect CPSC (Consumer Product Safety Commission) MCP to Pydantic AI

Create your Vinkius account to connect CPSC (Consumer Product Safety Commission) 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 CPSC (Consumer Product Safety Commission) with Pydantic AI

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Perplexity

Type-safe recall lookups for Pydantic AI

The `search_recalls` tool returns JSON that your agent immediately validates against a Pydantic model. If the government API returns unexpected fields, your agent catches it instantly. This prevents bad data from causing issues downstream. You get a reliable way to handle incoming safety information.

Fail fast with Pydantic AI validation

Your agent relies on strict types to process `search_recalls` output. If the response doesn't match your schema, the agent stops execution to prevent logic errors. It ensures your agent only acts on valid, well-formed safety data. You avoid the risks associated with loose data handling.

Model-agnostic safety checks in Pydantic AI

This MCP Server provides the same structured data regardless of the model you use. Your Pydantic AI agent maintains consistent validation logic across different LLMs. You build your safety logic once and reuse it. It keeps your codebase clean and focused on correctness.

Setup guide

Set up CPSC (Consumer Product Safety Commission) 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": {
        "cpsc-consumer-product-safety-commission-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent CPSC (Consumer Product Safety Commission) transactions")
print(result.output)

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Common questions about CPSC (Consumer Product Safety Commission) MCP in Pydantic AI

The agent raises a validation error immediately. This stops the execution flow, ensuring your application doesn't process corrupted safety information.

Yes, you should define a Pydantic class that mirrors the recall fields you need. The agent will then force the API output to match that structure.

Yes, all traffic is encrypted in transit. We treat the data as public, but we ensure the transport layer remains private and tamper-proof.

Yes, the tool is model-agnostic. You can connect it to local models just as easily as cloud-based ones.

Simply modify your Pydantic class definition. The agent will start enforcing the new schema on the next tool execution.

Use it with your favorite AI tools

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