CocktailFyi MCP Server for Pydantic AI 12 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect CocktailFyi 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 CocktailFyi "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in CocktailFyi?"
)
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 CocktailFyi MCP Server
Connect CocktailFyi, the comprehensive cocktail database, to any AI agent and explore hundreds of cocktail recipes, ingredients, bartending techniques, and educational guides through natural language.
Pydantic AI validates every CocktailFyi tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- Cocktail Recipes — Browse 600+ cocktails with complete recipes, ingredients, measurements, and step-by-step instructions
- Ingredient Database — Explore spirits, mixers, garnishes, and bitters used in cocktails
- Flavor Profiles — View sweetness, sourness, bitterness, and strength ratings for each cocktail
- Bartending Techniques — Learn when to shake, stir, muddle, or build a drink
- Educational Content — Access guides, glossary terms, and FAQs about mixology
- Search & Filter — Find cocktails by name, ingredient, or category
The CocktailFyi MCP Server exposes 12 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 CocktailFyi to Pydantic AI via MCP
Follow these steps to integrate the CocktailFyi 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 12 tools from CocktailFyi with type-safe schemas
Why Use Pydantic AI with the CocktailFyi MCP Server
Pydantic AI provides unique advantages when paired with CocktailFyi 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 CocktailFyi integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your CocktailFyi connection logic from agent behavior for testable, maintainable code
CocktailFyi + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the CocktailFyi MCP Server delivers measurable value.
Type-safe data pipelines: query CocktailFyi with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple CocktailFyi tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query CocktailFyi and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock CocktailFyi responses and write comprehensive agent tests
CocktailFyi MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect CocktailFyi to Pydantic AI via MCP:
get_cocktail
Get detailed cocktail information
get_cocktail_stats
Get CocktailFyi database statistics
get_cocktails_by_category
Get cocktails filtered by category
get_ingredient
Get detailed ingredient information
list_categories
List cocktail categories
list_cocktails
Each cocktail includes name, category, glass type, alcoholic status, difficulty, prep time, ABV, calories, flavor profile, ingredients, and instructions. List cocktails with pagination
list_faqs
List frequently asked questions about cocktails
list_glossary
List cocktail glossary terms
list_guides
List cocktail-making guides
list_ingredients
List all cocktail ingredients
list_techniques
with descriptions of when and how to use each. List cocktail preparation techniques
search_cocktails
Returns results matching the query term in cocktail names, ingredient names, or guide titles. Search cocktails by name or ingredients
Example Prompts for CocktailFyi in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with CocktailFyi immediately.
"Give me a classic Mojito recipe."
"What cocktails can I make with tequila?"
"What's the difference between shaking and stirring a cocktail?"
Troubleshooting CocktailFyi MCP Server with Pydantic AI
Common issues when connecting CocktailFyi to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCocktailFyi + Pydantic AI FAQ
Common questions about integrating CocktailFyi 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 CocktailFyi 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 CocktailFyi to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.