Compatible with every major AI agent and IDE
Get notebook on OneNote
Use this to dive deeper into a container's permissions or basic configurations. Get detailed properties of a specific notebook
Get page content on OneNote
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 on OneNote
Identifies primary containers necessary to navigate the hierarchical structure of OneNote. List all Microsoft OneNote notebooks
List pages on OneNote
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 on OneNote
Used for navigating highly complex, multi-layered textbook hierarchies inside OneNote. List section groups inside a specific notebook
List sections on OneNote
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 on OneNote
Useful when navigating deep, unindexed trees where discovering a particular keyword manually would exceed logic boundaries. Search page contents globally across all available notebooks
How Vinkius protects your data
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
How does the AI access my passwords and credentials?
It simply doesn't. On Vinkius, your passwords, API keys, and login details are kept in a secure vault. The AI (like ChatGPT or Claude) merely "asks" Vinkius to perform the task. Vinkius opens the door, does the work, and hands the result back to the AI. Your credentials are never seen, read, or learned by the artificial intelligence.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Can the integration delete entire extensive notebooks or important local sections?
No. The integration exclusively binds heavily to Reading methods (list, search, get) mapped safely alongside minimal Write interactions specifically scoped to Appending fresh notes. Destructive end-points are intrinsically restricted protecting vital long-term data persistently.
What can AI Agents do with OneNote?
Integrate OneNote to provide your custom AI agents with direct read and write access to the capabilities listed below.
Claude Code Integration for digital notebook
The OneNote MCP translates LLM intent into specific digital notebook actions. Agents like Cursor use this to interface securely with your industry titans infrastructure.
LLM Orchestration for content management
Build automated workflows involving content management by connecting OneNote. It provides Claude and ChatGPT with direct API hooks into your industry titans ecosystem.
OneNote. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
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.
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