# OneNote MCP > OneNote MCP connects your AI agent directly to Microsoft OneNote, treating your entire collection of notes like a single digital brain. Your agent can instantly search across thousands of pages, map complex notebook structures, and pull out raw text content without you ever leaving the chat interface. ## Overview - **Category:** industry-titans - **Price:** Free - **Tags:** digital-notebook, content-management, information-retrieval, document-organization, personal-knowledge-base ## Description Imagine having every meeting note, research citation, and brainstorm session stored in Microsoft OneNote suddenly accessible to your AI client. This MCP lets your agent dive into your personal or corporate notebooks like a librarian finding one specific card in a vast archive. Instead of manually clicking through nested sections and pages, you simply ask the question. Your agent then finds it—it searches global page content for keywords across all active notes, pulls out only the raw text from the relevant section, and even maps the entire structural hierarchy so you know exactly where everything lives. It's a huge time saver. You can get your AI client to append quick summaries or thoughts directly into an existing note right from our chat conversation. This capability turns OneNote from just storage into an active knowledge base. With Vinkius, this MCP gives your agent the deep context it needs to work with complex documents instantly. ## Tools ### list_notebooks Lists all primary notebooks available in your OneNote structure. ### get_notebook Retrieves detailed information about a specific, named notebook container. ### list_sections Finds all sections inside a given notebook, helping you narrow down the content scope. ### list_pages Lists metadata (titles and IDs) for every page within a specific section. ### get_page_content Extracts the actual written text content from one chosen page. ### search_pages Searches for a keyword or phrase across all your notebooks globally, instantly. ### list_section_groups Maps out multi-layered organizational groupings, useful for textbook or curriculum structures. ## Prompt Examples **Prompt:** ``` Search globally across my entire OneNote environment finding paragraphs explicitly mentioning Project Alpha. ``` **Response:** ``` Global search traversed. Found precisely 3 matches bounding inside the notebook '2023 Strategy'. One match points specifically within 'Q3 Objectives' page highlighting architectural boundaries. Shall I extract the explicit body content from that page locally? ``` **Prompt:** ``` List all active structural Notebooks visibly mapping currently in my domain. ``` **Response:** ``` Enumerated 4 main explicit organizational Notebooks natively. We observe 'Personal Notes', 'Work Reference Base', 'Marketing Meetings 24', and explicitly 'Drafts'. Would you like me to map the exact sections nested inside the 'Work Reference Base' specifically? ``` **Prompt:** ``` I need the exact written contents housed within page ID 1-3xx45... immediately. ``` **Response:** ``` Target page contents successfully dumped bounding natively. The text asserts a series of meeting notes dated Monday clearly outlining the revised UI design specifications and highlighting assigned sprint velocity points for backend devs gracefully logically ordered. I can summarize it entirely. ``` ## Capabilities ### Global Knowledge Search It searches across all your notebooks and pages for specific keywords or phrases, regardless of how deeply they are filed. ### Raw Text Extraction It pulls the plain written text from any single page, bypassing OneNote's complex formatting so you get clean data. ### Structural Mapping It generates a map of your entire organizational logic, listing notebooks, section groups, and sections in order. ### Content Appending You can send text blocks or summaries directly into an existing notebook section using the chat interface. ## Use Cases ### Finding the one meeting decision from six months ago A project lead needs to verify which team member agreed on the new API endpoint. Instead of opening dozens of old meeting notes, they ask their agent to `search_pages` for 'API endpoint agreement'. The agent instantly finds the correct paragraph across all notebooks and extracts it. ### Structuring a large research paper A researcher has citation notes scattered over years. They use the agent to `list_notebooks`, then map the structure using `list_section_groups`. This shows them all related sections, letting them quickly pull citations needed for a bibliography. ### Summarizing an executive update An assistant receives a massive document with notes from three different departments. They ask the agent to read the content and summarize it, using the appending feature to drop the final summary right into the 'Weekly Report' section. ### Archiving knowledge for future use A consultant finishes a major client project and needs to save all key decisions. They instruct the agent to gather notes from specific sections using `list_pages` first, then ask it to compile and append that clean text into a 'Project Archive' notebook. ## Benefits - Stop manual searching. Use the `search_pages` tool to find specific keywords across every notebook instantly, eliminating time spent clicking through folders. - Get clean data without formatting headaches. The `get_page_content` tool pulls raw text from any page, letting you process content exactly as plain text should be. - Map your entire knowledge base. By using `list_notebooks`, `list_section_groups`, and `list_sections`, your agent builds a complete structural map of your work. - Keep notes current. Use the built-in appending capability to send summaries or quick thoughts directly into an existing section from our chat conversation. - Deep dive into structure. The `list_pages` tool gives you metadata for all pages in a section, letting you index and reference content without needing to read every page first. ## How It Works The bottom line is that your AI agent treats your private OneNote files like a database it can query in real time. 1. First, enable this local MCP integration and provide your AI client with a Microsoft Graph Access Token scoped to OneNote. 2. Next, you simply write natural language commands into your agent, asking it to find specific information or map out your notes' structure. 3. The AI uses the connected tools to search the content, extract the text, or append new material, presenting only the actionable result back to you. ## Frequently Asked Questions **How does OneNote MCP search across my entire notebook?** The `search_pages` tool allows the agent to run a global keyword search across all your active notebooks simultaneously. This avoids searching just one section or one page at a time. **Is OneNote MCP suitable for reading images embedded in my notes?** The primary function is text extraction and searching, so it's best for written content. While the tool can index metadata, getting readable data requires specific tools like `get_page_content`. **Can I use OneNote MCP to create new notebooks?** The current scope focuses on reading and structuring existing notes. You must rely on native OneNote features to create brand-new containers; the MCP is for access, not creation. **How do I map out my entire corporate knowledge base using OneNote MCP?** You combine several tools: use `list_notebooks` first, then `list_section_groups`, and finally `list_sections`. The agent can traverse this structure to give you a complete organizational overview. **What is the difference between list_pages and get_page_content in OneNote MCP?** `list_pages` only retrieves metadata, giving you IDs and titles. `get_page_content`, however, performs the deeper action of retrieving the actual raw text written on that specific page.