WHOOP MCP Server for Pydantic AI 11 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect WHOOP 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 WHOOP "
"(11 tools)."
),
)
result = await agent.run(
"What tools are available in WHOOP?"
)
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 WHOOP MCP Server
Connect your WHOOP account to any AI agent and access your personal health data through natural conversation.
Pydantic AI validates every WHOOP tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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
- Profile — View your WHOOP profile and body measurements (height, weight, max HR)
- Cycles — Browse your 24-hour WHOOP cycles combining sleep, strain and recovery
- Sleep — Analyze sleep data with stages (light, deep, REM), duration and performance
- Recovery — Track recovery scores, HRV, resting heart rate and sleep balance
- Workouts — Review workout data with strain, heart rate zones, duration and calories
- Pagination — Navigate through historical data with date ranges and pagination tokens
The WHOOP MCP Server exposes 11 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 WHOOP to Pydantic AI via MCP
Follow these steps to integrate the WHOOP 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 11 tools from WHOOP with type-safe schemas
Why Use Pydantic AI with the WHOOP MCP Server
Pydantic AI provides unique advantages when paired with WHOOP 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 WHOOP integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your WHOOP connection logic from agent behavior for testable, maintainable code
WHOOP + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the WHOOP MCP Server delivers measurable value.
Type-safe data pipelines: query WHOOP with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple WHOOP tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query WHOOP and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock WHOOP responses and write comprehensive agent tests
WHOOP MCP Tools for Pydantic AI (11)
These 11 tools become available when you connect WHOOP to Pydantic AI via MCP:
get_body_measurement
Useful for tracking physical metrics alongside your WHOOP data. Get your body measurement data
get_cycle
Includes sleep, recovery, strain and heart rate metrics for that 24-hour period. Get a specific WHOOP cycle by ID
get_cycle_recovery
Includes recovery score, resting heart rate, HRV (heart rate variability), sleep balance and strain balance. Get recovery data for a specific WHOOP cycle
get_cycle_sleep
Includes sleep duration, stages (light, deep, REM, awake), disturbances and sleep performance percentage. Get sleep data for a specific WHOOP cycle
get_cycles
Cycles represent 24-hour periods of recovery and strain data. Each cycle includes sleep, recovery, strain and heart rate metrics. Supports date range filtering with start/end in ISO 8601 format. Pagination: max 25 results, use nextToken for more. Get your WHOOP cycle data
get_profile
Use this to verify your authentication is working and get your user ID for other endpoints. Get your WHOOP profile info
get_recovery
Supports date range filtering. Pagination: max 25 results per request. Get your WHOOP recovery data
get_sleep
Supports date range filtering. Pagination: max 25 results. Get your WHOOP sleep data
get_sleep_by_id
Includes full sleep stages, disturbances, respiratory rate and sleep performance. Get a specific WHOOP sleep record by ID
get_workout
Includes strain score, duration, heart rate zones, calories burned and GPS data if available. Get a specific WHOOP workout by ID
get_workouts
Supports date range filtering. Pagination: max 25 results. Get your WHOOP workout data
Example Prompts for WHOOP in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with WHOOP immediately.
"Show me my recovery score from today."
"How did I sleep last night?"
"Show me my workouts from this week."
Troubleshooting WHOOP MCP Server with Pydantic AI
Common issues when connecting WHOOP to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiWHOOP + Pydantic AI FAQ
Common questions about integrating WHOOP 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 WHOOP 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 WHOOP to Pydantic AI
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.