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eBay Seller MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect eBay Seller through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to eBay Seller "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in eBay Seller?"
    )
    print(result.data)

asyncio.run(main())
eBay Seller
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About eBay Seller MCP Server

Connect eBay Seller to any AI agent via MCP.

How to Connect eBay Seller to Pydantic AI via MCP

Follow these steps to integrate the eBay Seller MCP Server with Pydantic AI.

01

Install Pydantic AI

Run pip install pydantic-ai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 12 tools from eBay Seller with type-safe schemas

Why Use Pydantic AI with the eBay Seller MCP Server

Pydantic AI provides unique advantages when paired with eBay Seller through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your eBay Seller integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your eBay Seller connection logic from agent behavior for testable, maintainable code

eBay Seller + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the eBay Seller MCP Server delivers measurable value.

01

Type-safe data pipelines: query eBay Seller with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple eBay Seller tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query eBay Seller and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock eBay Seller responses and write comprehensive agent tests

eBay Seller MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect eBay Seller to Pydantic AI via MCP:

01

create_listing

Requires SKU (from inventory), listing title, category ID, pricing, format (FIXED_PRICE or AUCTION), and return/shipping policies. Returns listingId for management. Use this to make your inventory products visible to buyers. Create a new eBay listing for an inventory item

02

delete_inventory

Note: you cannot delete inventory items that have active listings. Use this to clean up discontinued products. Delete an inventory item by SKU

03

delete_listing

If there are active bids (auction), this may violate eBay policies. For fixed-price, this simply removes the item from sale. Use this to quickly remove unwanted inventory from the marketplace. Delete/end an eBay listing

04

get_account_info

Use this to verify account status or display seller metrics. Get your eBay seller account information and feedback score

05

get_inventory_item

Use this to verify product details before updating or creating listings. Get detailed information for a specific inventory item by SKU

06

get_order_details

Use this to verify order contents before packing and shipping. Get detailed information for a specific order

07

get_orders

Optional filter parameter accepts criteria like "creationDate:[2024-01-01..2024-12-31]", "orderFulfillmentStatus:NOT_STARTED". Use this to manage order fulfillment pipeline. List recent orders with optional filtering

08

list_inventory

Each item includes SKU, title, condition, and available quantity. Use optional limit (default 50) and offset for pagination. Essential for reviewing stock levels. List all inventory items with SKUs, titles, and available quantities

09

list_listings

Each listing includes title, price, status, listing ID, and associated SKU. Use this to review what is currently live on eBay or recently ended. List active eBay listings for your store

10

ship_order

Updates buyer with shipping notification. Requires orderId, lineItemId, carrier name (e.g., "USPS", "FedEx", "UPS"), and tracking number. Use this to confirm shipment and complete the order cycle. Mark an order as shipped with carrier and tracking number

11

update_inventory

Requires SKU, title, condition, and product details (brand, MPN, UPC/EAN, description). Also updates stock quantity and pricing. Use this to manage your product catalog before listing items for sale. Update or create an inventory item with product details and stock quantity

12

update_listing

Note: certain fields cannot be changed once listing is active. Use this to adjust pricing or correct listing errors. Update an existing eBay listing (price, title, details)

Troubleshooting eBay Seller MCP Server with Pydantic AI

Common issues when connecting eBay Seller to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

eBay Seller + Pydantic AI FAQ

Common questions about integrating eBay Seller MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your eBay Seller MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

Connect eBay Seller to Pydantic AI

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.