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eBay Shopper MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect eBay Shopper 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 Shopper "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())
eBay Shopper
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About eBay Shopper MCP Server

Connect eBay Shopper to any AI agent via MCP.

How to Connect eBay Shopper to Pydantic AI via MCP

Follow these steps to integrate the eBay Shopper 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 10 tools from eBay Shopper with type-safe schemas

Why Use Pydantic AI with the eBay Shopper MCP Server

Pydantic AI provides unique advantages when paired with eBay Shopper 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 Shopper 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 Shopper connection logic from agent behavior for testable, maintainable code

eBay Shopper + Pydantic AI Use Cases

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

01

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

02

API orchestration: chain multiple eBay Shopper 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 Shopper and output structured, schema-compliant notifications

04

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

eBay Shopper MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect eBay Shopper to Pydantic AI via MCP:

01

get_categories

Optional parentId filters to subcategories. Use this to discover available categories or navigate the eBay catalog structure. List eBay product categories and subcategories

02

get_item_compatibility

Essential for auto parts buyers to verify fitment before purchase. Get vehicle compatibility information for an auto parts listing

03

get_item_details

The itemId is obtained from search results. Use this to get complete product specs before purchasing or comparing. Get full details for a specific eBay item by its ID

04

get_item_rating

Use this for a quick quality assessment without reading individual reviews. Get aggregated rating summary for an eBay item

05

get_item_reviews

Returns rating (1-5), review text, reviewer name, and date. Use this to assess product quality and customer satisfaction before buying. Get customer reviews and ratings for a specific eBay item

06

get_merchant_item_details

Similar to get_item_details but with merchant-focused data. Use this for inventory research. Get item details from the merchant perspective

07

get_shipping_estimate

Use this to calculate total cost before buying. Get estimated shipping cost and delivery date for an item

08

search_by_category

g., Electronics, Fashion, Motors). Requires categoryId from get_categories endpoint. Useful for browsing specific sections of eBay. Search for items within a specific eBay category

09

search_by_image

Useful when you know what something looks like but not its name or model. Returns visually similar items with prices and details. Search eBay for visually similar items using an image URL

10

search_items

Returns a list of matching items with title, price, condition, image URL, and item ID. Use optional parameters: limit (max 10), offset (pagination), sort (BestMatch, price, etc.). Ideal for finding products, comparing prices, or discovering available inventory. Search for items on eBay by keyword, brand, or product name

Troubleshooting eBay Shopper MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

eBay Shopper + Pydantic AI FAQ

Common questions about integrating eBay Shopper 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 Shopper MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

Connect eBay Shopper to Pydantic AI

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.