How to Use the Vestiaire Collective MCP in Pydantic AI

Q: How do I check item details using Pydantic AI on Vestiaire Collective?

You execute getitemdetails. Because this server is validated by Pydantic, you receive a guaranteed structure containing the brand, size, material, and authentication status of the article.

Q: Can I check my inventory using Pydantic AI on Vestiaire Collective?

Yes. The listmysellingitems tool provides a structured list of all your currently active listings. It's designed to return predictable data about your available items.

Q: What data types does this MCP Server touch regarding data privacy?

This server handles user listing metadata and inventory records. The specific data points include item ID, brand name, condition status, size, material type, and current list price.

Q: What is the best way to search for goods on Vestiaire Collective using Pydantic AI?

The searchwithadvancedfilters tool provides maximum control. It allows you to pass structured parameters like color, material, and price range, ensuring the returned data always matches your expected schema.

Q: Do I need help listing available brands on Vestiaire Collective using Pydantic AI?

Use listavailablebrands. This tool returns a validated list of all luxury brand names, which is essential for populating structured search forms or dropdown menus.

Validate structured luxury fashion data from Vestiaire Collective using Pydantic AI.

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Connect Vestiaire Collective MCP to Pydantic AI

Create your Vinkius account to connect Vestiaire Collective 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 Vestiaire Collective with Pydantic AI

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Structured item analysis

When you use `get_item_details`, your agent doesn't just get raw text; it gets validated fields for brand, condition, authentication status, size, material, and price vs. new retail. The output is guaranteed to be correct. The pricing context is managed by `analyze_price_trends`. This function requires structured input about brands or categories, returning predictable data on historical market trends. You never have to guess what format the result will take.

Identifying available goods

The agent uses `list_catalog_categories` to fetch a defined list of all product types—bags, shoes, clothes, accessories, jewelry, watches. This structured output is perfect for building internal taxonomies. The toolset also exposes lists from `list_available_brands` and `list_available_designers`. These functions give you validated arrays of names and collections available on Vestiaire Collective.

Targeted item discovery

For granular searches, use `search_by_brand`. You pass the brand name (a structured string) and an optional category ID. The resulting data set is clean and predictable. The most flexible option is combining filters using `search_with_advanced_filters`. Because Pydantic validates the response, you know exactly which fields—color, state, material, price—you're getting back, no matter how complex the filter set.

Setup guide

Set up Vestiaire Collective 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": {
        "vestiaire-collective-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vestiaire Collective. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Vestiaire Collective MCP in Pydantic AI

You execute `get_item_details`. Because this server is validated by Pydantic, you receive a guaranteed structure containing the brand, size, material, and authentication status of the article.

Yes. The `list_my_selling_items` tool provides a structured list of all your currently active listings. It's designed to return predictable data about your available items.

This server handles **user listing metadata** and **inventory records**. The specific data points include item ID, brand name, condition status, size, material type, and current list price.

The `search_with_advanced_filters` tool provides maximum control. It allows you to pass structured parameters like color, material, and price range, ensuring the returned data always matches your expected schema.

Use `list_available_brands`. This tool returns a validated list of all luxury brand names, which is essential for populating structured search forms or dropdown menus.

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