OneNote MCP Server for Pydantic AI 7 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OneNote 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 OneNote "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in OneNote?"
)
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 OneNote MCP Server
Empower your conversational AI with omniscient access to your Microsoft OneNote digital brain. Transform how you organize information by linking an AI agent capable of drilling into deep notebooks, parsing hidden sections, explicitly searching across thousands of pages organically, and seamlessly capturing new notes from the chat interface without switching tabs.
Pydantic AI validates every OneNote tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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
- Deep Search & Indexing — Invoke robust global searches discovering specific keywords across all active Notebook domains instantly without waiting for native indexing.
- Page Content Extraction — Drill cleanly into specific distinct Pages fetching raw text securely preventing you from hunting through nested hierarchies manually.
- Workspace Navigation — List structural trees mapping your distinct Notebooks, Section Groups, and Sections cleanly traversing your organizational logic entirely.
- Content Appending — Dispatch text blocks, parsed summaries, or quick thoughts into existing notebook sections cleanly right from the LLM prompt conversationally.
The OneNote MCP Server exposes 7 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 OneNote to Pydantic AI via MCP
Follow these steps to integrate the OneNote 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 7 tools from OneNote with type-safe schemas
Why Use Pydantic AI with the OneNote MCP Server
Pydantic AI provides unique advantages when paired with OneNote 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 OneNote integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your OneNote connection logic from agent behavior for testable, maintainable code
OneNote + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the OneNote MCP Server delivers measurable value.
Type-safe data pipelines: query OneNote with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple OneNote tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query OneNote and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock OneNote responses and write comprehensive agent tests
OneNote MCP Tools for Pydantic AI (7)
These 7 tools become available when you connect OneNote to Pydantic AI via MCP:
get_notebook
Use this to dive deeper into a container's permissions or basic configurations. Get detailed properties of a specific notebook
get_page_content
By default, OneNote pages are serialized using complex Microsoft Graph HTML formats with proprietary tags. Use this to ingest the actual written text or data. Retrieve the exact raw HTML content of a single page
list_notebooks
Identifies primary containers necessary to navigate the hierarchical structure of OneNote. List all Microsoft OneNote notebooks
list_pages
Results include the bare page metadata (IDs, titles, timestamps), but notably DO NOT include the heavy internal raw HTML content. Used for structural indexing. List all pages contained within a specific section
list_section_groups
Used for navigating highly complex, multi-layered textbook hierarchies inside OneNote. List section groups inside a specific notebook
list_sections
Sections act as the folders containing the raw pages. Requires passing the parent Notebook ID to query the correct topological children. List all sections contained within a specific notebook
search_pages
Useful when navigating deep, unindexed trees where discovering a particular keyword manually would exceed logic boundaries. Search page contents globally across all available notebooks
Example Prompts for OneNote in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with OneNote immediately.
"Search globally across my entire OneNote environment finding paragraphs explicitly mentioning Project Alpha."
"List all active structural Notebooks visibly mapping currently in my domain."
"I need the exact written contents housed within page ID 1-3xx45... immediately."
Troubleshooting OneNote MCP Server with Pydantic AI
Common issues when connecting OneNote to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiOneNote + Pydantic AI FAQ
Common questions about integrating OneNote 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 OneNote 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 OneNote to Pydantic AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.