Vestiaire Collective MCP Server for Pydantic AI 9 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Vestiaire Collective through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Vestiaire Collective "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in Vestiaire Collective?"
)
print(result.data)
asyncio.run(main())
* 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 Vestiaire Collective MCP Server
Connect your Vestiaire Collective seller account to any AI agent and take full control of your luxury resale business through natural conversation.
Pydantic AI validates every Vestiaire Collective tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Luxury Search — Find authenticated luxury items from brands like Hermès, Chanel, Louis Vuitton, and Gucci with precision
- Advanced Filters — Search by brand, category, condition, price range, color, and material to find exactly what you're looking for
- Price Analysis — Analyze market trends and resale value for specific luxury brands and categories to optimize your pricing
- Inventory Management — List and track your own selling items and dressing room status directly from your agent
- Catalog Discovery — Browse available brands, designers, and categories within the vast Vestiaire Collective catalog
- Authentication & Details — Retrieve full metadata for items including condition, price history vs. new, and material details
The Vestiaire Collective MCP Server exposes 9 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Vestiaire Collective to Pydantic AI via MCP
Follow these steps to integrate the Vestiaire Collective MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from Vestiaire Collective with type-safe schemas
Why Use Pydantic AI with the Vestiaire Collective MCP Server
Pydantic AI provides unique advantages when paired with Vestiaire Collective through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Vestiaire Collective integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Vestiaire Collective connection logic from agent behavior for testable, maintainable code
Vestiaire Collective + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Vestiaire Collective MCP Server delivers measurable value.
Type-safe data pipelines: query Vestiaire Collective with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Vestiaire Collective tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Vestiaire Collective and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Vestiaire Collective responses and write comprehensive agent tests
Vestiaire Collective MCP Tools for Pydantic AI (9)
These 9 tools become available when you connect Vestiaire Collective to Pydantic AI via MCP:
analyze_price_trends
Analyser les tendances de prix pour une marque et catégorie (valorisation du luxe)
get_item_details
Consulter un article : marque, état, authentification, prix vs. neuf, taille, matière
list_available_brands
Lister les marques de luxe disponibles (Hermès, Chanel, Louis Vuitton, Dior, etc.)
list_available_designers
Lister les créateurs et collections
list_catalog_categories
Lister les catégories (sacs, chaussures, vêtements, accessoires, bijoux, montres)
list_my_selling_items
Consulter les articles en vente dans votre dressing
search_by_brand
) et catégorie. Rechercher par marque de luxe et catégorie optionnelle
search_luxury_items
Fournissez une requête textuelle. Rechercher des articles de luxe par mots-clés (ex : "Hermès Birkin", "Chanel tweed")
search_with_advanced_filters
Fournissez les filtres sous forme de paramètres. Recherche avancée avec filtres multiples : marque, état, prix, couleur, matière, pays
Example Prompts for Vestiaire Collective in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Vestiaire Collective immediately.
"Search for vintage Hermès Birkin bags in very good condition under 15000 EUR."
"What is the current resale trend for Chanel Flap Bags?"
"List all items I currently have for sale."
Troubleshooting Vestiaire Collective MCP Server with Pydantic AI
Common issues when connecting Vestiaire Collective to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiVestiaire Collective + Pydantic AI FAQ
Common questions about integrating Vestiaire Collective MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Vestiaire Collective with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Vestiaire Collective to Pydantic AI
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.