Doodle MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Doodle 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 Doodle "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Doodle?"
)
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 Doodle MCP Server
Connect your Doodle account to any AI agent and take full control of your group scheduling and meeting polls through natural conversation.
Pydantic AI validates every Doodle tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Poll Orchestration — List all Doodle polls and retrieve explicitly attached array vectors representing titles, states (OPEN/CLOSED), and final chosen options
- Live Poll Creation — Provision new group scheduling polls by commanding absolute explicit text payloads for specific dates and times
- Participant Auditing — Enumerate explicitly attached user responses active within any target poll to identify precisely who has voted
- Programmatic Voting — Trigger absolute response routing to add or remove participant votes, mapping literal preference arrays (Yes, No, If-need-be) exactly
- Collaboration Oversight — Retrieve and append string chats and contextual comments attached to specific poll IDs to verify participant feedback
- State Management — Change poll states to CLOSED to lock participation arrays and override core settings to dictate finally which exact option won
- Data Invalidation — Irreversibly vaporize explicit poll entities and wipe all associated votes and comments from the system permanently
The Doodle MCP Server exposes 10 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 Doodle to Pydantic AI via MCP
Follow these steps to integrate the Doodle 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 10 tools from Doodle with type-safe schemas
Why Use Pydantic AI with the Doodle MCP Server
Pydantic AI provides unique advantages when paired with Doodle 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 Doodle integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Doodle connection logic from agent behavior for testable, maintainable code
Doodle + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Doodle MCP Server delivers measurable value.
Type-safe data pipelines: query Doodle with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Doodle tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Doodle and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Doodle responses and write comprehensive agent tests
Doodle MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Doodle to Pydantic AI via MCP:
add_comment
Add a comment to a Doodle poll
add_participant
Provide a name and preference array (0=no, 1=yes, 2=if-need-be) matching option quantities. Add a participant vote to a Doodle poll programmatically
close_poll
Overrides the core settings dictating finally which exact option value string won. Close a Doodle poll and set the final chosen option
create_poll
Participants will be invited to vote on their preferred options. Create a new Doodle poll for group scheduling
delete_poll
Drops the raw data out of the system returning completely blank state. Permanently delete a Doodle poll and all associated participant votes and comments
get_comments
Retrieve all comments on a Doodle poll
get_poll
Retrieve detailed information for a specific Doodle poll by ID
list_participants
List all participants who voted on a Doodle poll
list_polls
Returns poll titles, states (OPEN/CLOSED), creation dates, number of participants, and chosen final options. List all Doodle polls created by the authenticated user
remove_participant
The core system inherently recalculates the total votes autonomously. Remove a participant and their votes from a Doodle poll
Example Prompts for Doodle in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Doodle immediately.
"List my Doodle polls"
"Create a poll 'Launch Sync' with options: 'Monday 10am', 'Tuesday 2pm'"
"Who has voted on the 'Team Offsite' poll?"
Troubleshooting Doodle MCP Server with Pydantic AI
Common issues when connecting Doodle to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDoodle + Pydantic AI FAQ
Common questions about integrating Doodle 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 Doodle 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 Doodle to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.