How to Use the Skydropx API MCP in Pydantic AI

Q: Can I reliably list all shipments with Skydropx API and Pydantic AI?

Yes. When calling listshipments, the agent validates that every returned shipment record contains predictable fields like tracking IDs and dates, making your downstream code rock solid.

Q: What is the process for finding current package statuses with Skydropx API and Pydantic AI?

Use gettracking. Because of runtime validation, you're guaranteed that the tracking data returned—like status messages or last known coordinates—will match your defined model.

Q: How does Skydropx API handle multiple location checks with Pydantic AI?

You can use listlocations and listpackages. The agent validates that the data pulled from these tools—like warehouse IDs or package template names—are correctly typed for subsequent operations.

Type-safe shipping with Pydantic AI. Guarantees correct labels across LatAm.

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Connect Skydropx API MCP to Pydantic AI

Create your Vinkius account to connect Skydropx API to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Skydropx API with Pydantic AI

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Claude

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Gemini

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Validate carrier rates on the fly.

Before you commit to a price, check it first using `get_quotation`. The agent validates that the returned data structure matches expected types. No surprise fields here. This is vital when comparing multiple carriers listed by `list_carriers`, ensuring your comparison logic doesn't fail due to unexpected API responses.

Creating and managing labels safely.

When you run `create_label`, Pydantic AI validates the output structure. If Skydropx API returns a label record that's malformed, your agent fails loudly—you know exactly what broke. If you need to remove an active label using `cancel_label`, the tool confirms the necessary fields were present and valid before proceeding.

Logging package details reliably.

Need a standard box size? Use `create_package` to register it. The agent ensures that this template data adheres strictly to your defined Pydantic models, preventing runtime errors. Likewise, when listing existing packages with `list_packages`, the structure of the returned list is guaranteed to be correct.

Setup guide

Set up Skydropx API 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": {
        "skydropx-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Skydropx API MCP in Pydantic AI

Pydantic AI validates every response from the MCP Server. This means if `get_quotation` gives you unexpected JSON, the agent throws a specific validation error, not just garbage data.

Yes. When calling `list_shipments`, the agent validates that every returned shipment record contains predictable fields like tracking IDs and dates, making your downstream code rock solid.

Use `get_tracking`. Because of runtime validation, you're guaranteed that the tracking data returned—like status messages or last known coordinates—will match your defined model.

You can use `list_locations` and `list_packages`. The agent validates that the data pulled from these tools—like warehouse IDs or package template names—are correctly typed for subsequent operations.

This server handles tracking and shipment metadata, specifically destination addresses and required customs documentation. The agent treats these fields as strictly typed strings or objects.

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