Wine-Searcher MCP Server for Pydantic AI 6 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Wine-Searcher through 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 Wine-Searcher "
"(6 tools)."
),
)
result = await agent.run(
"What tools are available in Wine-Searcher?"
)
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 Wine-Searcher MCP Server
Connect to Wine-Searcher — the world's largest wine price comparison engine — and access real-time market intelligence for any wine.
Pydantic AI validates every Wine-Searcher tool response against typed schemas, catching data inconsistencies at build time. Connect 6 tools through 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
- Wine Check — Look up any wine: critic scores, grape varieties, region, alcohol content, and global average/min/max pricing
- Market Price — Compare real-time pricing from 100,000+ merchants: shop names, locations, and direct purchase URLs
- Search Wines — Full-text search across the entire Wine-Searcher database for discovery and exploration
- Grape Info — Detailed grape variety profiles: origins, growing regions, wine styles, and food pairings
- Region Info — Wine region deep-dives: climate, soil, appellations, and notable producers
- Producer Info — Winery profiles: key wines, price ranges, scores, and available vintages
The Wine-Searcher MCP Server exposes 6 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 Wine-Searcher to Pydantic AI via MCP
Follow these steps to integrate the Wine-Searcher 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 6 tools from Wine-Searcher with type-safe schemas
Why Use Pydantic AI with the Wine-Searcher MCP Server
Pydantic AI provides unique advantages when paired with Wine-Searcher 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 Wine-Searcher integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Wine-Searcher connection logic from agent behavior for testable, maintainable code
Wine-Searcher + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Wine-Searcher MCP Server delivers measurable value.
Type-safe data pipelines: query Wine-Searcher with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Wine-Searcher tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Wine-Searcher and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Wine-Searcher responses and write comprehensive agent tests
Wine-Searcher MCP Tools for Pydantic AI (6)
These 6 tools become available when you connect Wine-Searcher to Pydantic AI via MCP:
grape_info
Perfect for sommelier education and pairing recommendations. Get grape variety info
market_price
Use for price comparison, market analysis, or finding the best deal on a specific wine. Get global market pricing
producer_info
Use for winery research and brand comparison. Get producer/winery info
region_info
Essential for terroir education and regional exploration. Get wine region info
search_wines
Returns matching wines with pricing, scores, and merchant availability. Use for discovery and exploration. Search the wine database
wine_check
), grape varieties, region, appellation, alcohol content, average/min/max pricing across global merchants. The primary lookup tool for any wine question. Check wine details and scores
Example Prompts for Wine-Searcher in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Wine-Searcher immediately.
"What's the average price for Opus One 2021?"
"Find merchants near London selling Dom Pérignon 2012."
"What can you tell me about the Pomerol wine region?"
Troubleshooting Wine-Searcher MCP Server with Pydantic AI
Common issues when connecting Wine-Searcher to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiWine-Searcher + Pydantic AI FAQ
Common questions about integrating Wine-Searcher 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 Wine-Searcher 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 Wine-Searcher to Pydantic AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.