How to Use the Easyship MCP in Pydantic AI

Q: How do I connect the Easyship MCP Server to my Pydantic AI agent?

Use the MCPToolset class with your Vinkius HTTP URL to load the tools into your agent. This registers tools like geteasyshipaccountmetadata as fully typed functions that your agent can execute.

Q: What makes Pydantic AI better for managing Easyship rates?

It prevents silent errors by validating the output of getshippingrates against strict Python types. If a courier returns an invalid rate format, Pydantic AI raises a validation error instead of letting your agent hallucinate a price.

Q: Can I use Pydantic AI to track failed Easyship deliveries?

Yes, your agent can call listfaileddeliveries to get a list of problematic shipments. The framework validates the response structure, ensuring your agent can reliably parse the failure reasons and update your database.

Ensure type-safe shipping operations by validating your Easyship MCP Server data with Pydantic AI.

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Connect Easyship MCP to Pydantic AI

Create your Vinkius account to connect Easyship 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 Easyship with Pydantic AI

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Type-safe rate calculation with Pydantic AI

This MCP Server exposes `get_shipping_rates` to your Pydantic AI agent, guaranteeing that every returned rate matches your strict data models. If the API returns a malformed currency or an unexpected structure, the framework fails loudly before any bad data spreads. The agent uses `list_available_couriers` to fetch carrier profiles and map them directly to Pydantic schemas. This ensures your application always operates with structured, verified courier data, regardless of which LLM you use.

Strict validation for shipment tracking and audits

The `get_shipment_details` tool allows your Pydantic AI agent to retrieve tracking information with absolute type safety. Every field, from the tracking number to the transit history, is validated against your runtime schemas. When auditing performance, the agent calls `quick_shipping_volume_audit` to get a structured summary of your shipment activity. Because the data is strictly validated, you can safely use it to feed downstream accounting and inventory systems.

Reliable shipment searching and exception tracking

Using `search_shipments_by_reference`, your Pydantic AI agent can search for orders without risking type errors from messy search queries. The framework validates the search parameters before hitting the API, catching bugs early. To handle delivery exceptions, the agent queries `list_failed_deliveries` to identify stuck packages. It parses the results into strict error-handling models, allowing your application to trigger automated recovery workflows safely.

Setup guide

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

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

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

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Common questions about Easyship MCP in Pydantic AI

Use the `MCPToolset` class with your Vinkius HTTP URL to load the tools into your agent. This registers tools like `get_easyship_account_metadata` as fully typed functions that your agent can execute.

It prevents silent errors by validating the output of `get_shipping_rates` against strict Python types. If a courier returns an invalid rate format, Pydantic AI raises a validation error instead of letting your agent hallucinate a price.

Yes, your agent can call `list_failed_deliveries` to get a list of problematic shipments. The framework validates the response structure, ensuring your agent can reliably parse the failure reasons and update your database.

Yes, the MCP server running on Vinkius supports both streamable HTTP and SSE transports. Your Pydantic AI agent can connect to either transport, depending on your production deployment requirements.

Your account metadata and API keys are stored securely within Vinkius's zero-trust environment. Pydantic AI only handles the validated runtime payloads, and all communication is encrypted over HTTPS, keeping your shipping credentials completely isolated.

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