# Bear MCP for AI Agents AI Agent Connect > Bear MCP lets you connect your Bear notes to your AI agent. You can search, read, and organize your entire markdown knowledge base using natural language. It handles tasks like moving notes to the archive, renaming tags, and injecting text into existing notes without you having to do the manual heavy lifting. ## Overview - **Category:** productivity - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_TLQxZBRzGLnr7TZkljxUEGdAXpbyLHKIFiqqZEvb/ai-agent-connect - **Tags:** markdown, personal-knowledge-base, document-management, offline-storage, text-editing ## Description This Bear MCP connects your personal knowledge base to your AI client so you can interact with your notes like a conversation. Instead of digging through folders or remembering which note has that specific piece of research, you just ask your agent to find it. It handles the heavy lifting of reading through full markdown files and pulling out the exact bits you need for your current task. You can tell your agent to organize your workspace by moving old drafts into the trash or archiving research projects that are no longer active. It even lets you manage your taxonomy, so if you need to rename a tag across thousands of notes, the agent does it in one go without you having to edit each one manually. Because Vinkius makes it easy to manage these connections, you can keep your thinking graph updated and your information organized without leaving your current workspace. It's built for people who have a lot of fragmented thoughts and need a way to assemble them into finished drafts or find specific code snippets from months ago. Whether you're pulling out a specific configuration block for a dev project or summarizing a month of research, this connection makes your notes feel like a living, searchable extension of your own mind. ## Tools ### search_notes Search across all Bear app notes. This finds notes based on content, titles, or specific tags like @todo. ### create_note Create a new native Bear note. This lets your agent start a new document with a title and specific tags. ### add_text Append or prepend Markdown chunks to a Bear note. This lets you add info to a note without overwriting what is already there. ### trash_note Move an explicit Bear Note to the Trash. Use this to clean up your workspace by removing discarded drafts. ### archive_note Archive an explicit Bear Note. This moves notes out of your active view while keeping them searchable. ### list_tags Retrieve the exact Tags taxonomy nesting globally. This helps your agent understand your folder-like tag structure. ### open_tag List all explicit Bear notes matching a specific tag. Use this to quickly see every note related to a specific topic. ### rename_tag Rename globally an entire tag across all mapped Notes. This fixes taxonomy issues across your whole library instantly. ### delete_tag Destroy entirely a Tag constraint globally. Use this to remove tags that are no longer needed in your system. ### open_note Retrieve explicit complete Markdown content of a Bear note. This gives your agent the full text of a note to analyze. ## Prompt Examples **Prompt:** ``` Find my notes about the 2026 migration and summarize the key risks. ``` **Response:** ``` I found 3 notes related to 'Database Migration 2026'. Here are the key risks identified in the 'Q1 Migration Plan' document: | Risk | Description | | :--- | :--- | | Data Loss | Potential during the schema swap | | Downtime | Estimated 15 minutes for the migration | Would you like me to open the full note for more details? ``` **Prompt:** ``` Rename the tag #drafts to #completed_projects across everything. ``` **Response:** ``` I've updated your library. Every instance of the tag #drafts has been renamed to #completed_projects. This change is now live across all your notes. ``` **Prompt:** ``` Create a new note for today's meeting and tag it with work/meetings. ``` **Response:** ``` I've created a new note titled 'Meeting Notes - App V2' and added the tag 'work/meetings/vurb'. It's now synced to your Bear app. ``` ## Capabilities ### Query your entire library Your agent can search through all your notes based on content, titles, or specific tags. ### Read full markdown content The agent can pull the complete text of any note to analyze or summarize for you. ### Inject text into notes You can have your agent append or prepend new information to existing notes automatically. ### Automate lifecycle management Move old research to the archive or delete discarded drafts with simple voice or text commands. ### Manage global tags Rename or delete tags across your entire library to keep your taxonomy clean. ### Create new notes instantly Have your agent start new documents with specific titles and tags based on your conversation. ## Use Cases ### Summarizing research archives A researcher has 50 notes on 'Quantum Computing' and needs a summary. The agent uses `search_notes` and `open_note` to read them all and write a summary. ### Bulk renaming project tags A dev needs to rename a project tag from 'Old_App' to 'Legacy_App'. The agent uses `rename_tag` to update every note across the database. ### Injecting snippets into drafts A writer wants to add a new paragraph to a draft. The agent uses `add_text` to append the new content to the correct note. ### Automated archive cleanup A user wants to clear out old meeting notes. The agent uses `archive_note` to move all notes with the 'Meeting' tag to the archive. ## Benefits - Stop manual copy-pasting by using `add_text` to inject information directly into your existing notes. - Keep your workspace clean by having your agent use `archive_note` and `trash_note` to manage your lifecycle. - Fix broken taxonomies instantly with `rename_tag` which updates every single note in your library at once. - Find specific information faster by using `search_notes` to query your entire markdown history. - Build better drafts by having your agent use `open_note` to read full content and `create_note` to start new ones. ## How It Works The bottom line is your agent gets full read and write access to your Bear notes for instant information retrieval and organization. 1. Subscribe to the Bear MCP on the Vinkius marketplace. 2. Provide your Bear API Token to link your local instance. 3. Ask your agent to find, edit, or organize your notes using natural language. ## Frequently Asked Questions **Can the Bear MCP read my full notes?** Yes, it can fetch the full markdown content of any specific note. This allows your agent to analyze the entire document to answer questions or summarize information. **Will this Connector help me organize my tags?** Absolutely. It can rename tags globally across your entire library, allowing you to fix taxonomy issues in one step instead of editing every note manually. **Can I use Bear MCP to move notes to the archive?** Yes, you can command your agent to move specific notes to the archive or trash. This helps keep your active workspace clean of old research or drafts. **How does Bear MCP handle new notes?** Your agent can create new native Bear notes for you. You just tell it what the title should be and what tags to apply, and it handles the creation instantly. **Can the Bear MCP search for specific tags?** Yes, it can search your entire Bear app for notes matching specific tags. This makes it easy to find all notes related to a specific project or topic. **Is my Bear data safe with this Connector?** The Connector connects directly to your private local instance using your Bear API Token. Your data remains private and is only accessed by your agent when you give it instructions. **Can the AI precisely update a note without overwriting its entire content?** Yes. It uses the `add_text` mutation tool, seamlessly attaching blocks of text to either the absolute bottom (append) or the explicit top (prepend) of the given UUID note, leaving the core intact. **Does it understand nested tags (like #work/design/logo)?** Bear relies heavily on tagging workflows. The agent natively queries and navigates explicit sub-tag pathways exactly like the application UI, mapping out your distinct taxonomy rules efficiently. **Can it search for uncompleted action items across many notes?** Simply ask the agent to search for the specialized string '@todo'. Bear exposes these native markers directly via the API, returning every unique UUID containing a matching string checklist efficiently.