Amplenote MCP. Turn your notes and tasks into conversational data.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Amplenote MCP Server connects your Amplenote workspace directly to your AI agent. Search notes, manage tasks, and organize ideas using natural language prompts.
You can retrieve specific notes, list all tasks, create new documentation, or update task statuses—all without leaving your chat window.
It's your entire personal knowledge base, accessible via API calls.
What your AI agents can do
Create note
Creates a new note by providing a title and the Markdown content.
Create task
Adds a new actionable item, which can be tracked with due dates and priorities.
Delete note
Permanently removes a note using its unique identifier.
The agent performs a full-text search across all notes and tasks in your Amplenote vault, pulling relevant content directly into the conversation.
You instruct the agent to draft a new note, supplying a title and Markdown body, which gets saved to your Amplenote account.
The agent can list all tasks, retrieve specific tasks by ID, or update a task's status and content.
The agent lists all available tags and the tag hierarchy, giving it a map of your knowledge taxonomy.
You can pull the full content of a single note by UUID, or update its title and body text.
The agent checks a specific note to see what operations (like sharing or printing) are available on it.
Ask AI about this MCP
Supported MCP Clients
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Amplenote MCP Server: 12 Tools for Knowledge & Task Management
These tools let your AI client create, read, update, and search every note and task in your Amplenote workspace.
019d754dcreate note
Creates a new note by providing a title and the Markdown content.
019d754dcreate task
Adds a new actionable item, which can be tracked with due dates and priorities.
019d754ddelete note
Permanently removes a note using its unique identifier.
019d754dget note
Retrieves the full text and metadata for a specific note using its UUID.
019d754dget note actions
Lists all operations that can be performed on a given note.
019d754dget task
Retrieves the details of a single task by its ID.
019d754dlist notes
Lists every note in the Amplenote workspace.
019d754dlist tags
Shows all tags used across notes and tasks, helping you map your knowledge taxonomy.
019d754dlist tasks
Lists all tasks across all notes, showing status, due dates, and parent notes.
019d754dsearch notes
Performs a full-text search across every note and task using keywords.
019d754dupdate note
Modifies the title and/or body content of an existing note by its UUID.
019d754dupdate task
Changes the content, completion status, or other properties of a specific task.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Amplenote, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
The Amplenote MCP Server connects your Amplenote workspace right into your AI agent. You'll search your notes, manage tasks, and organize ideas using natural language prompts. You can pull specific notes, list all your tasks, create new docs, or update a task's status—all without leaving your chat window. It's your whole personal knowledge base, accessed via API calls. You've got the power to search_notes to run a full-text search across every note and task in your Amplenote vault, pulling relevant content right into the conversation. You can list_notes to see every note in the workspace, and list_tasks to get a full rundown of all tasks, including their status, due dates, and parent notes. Need to dig into one specific note? get_note retrieves the full text and metadata for a note using its UUID. If you wanna find out what's happening with a single task, get_task pulls up the details for that task by its ID. You can also list_tags to show all tags used across notes and tasks, which helps you map out your knowledge taxonomy. Want to write something new? You'll create_note by giving it a title and the Markdown content. If you gotta clean up a note, you can update_note by modifying the title and/or body content of an existing note using its UUID. If you need to delete a note for good, delete_note permanently removes it using its unique identifier. For tasks, you can create_task to add a new actionable item, tracking it with due dates and priorities. If a task changes, you use update_task to change its content, completion status, or other properties for a specific task. If you're looking at a note and wanna know what you can do with it, get_note_actions lists all available operations on that note. You've got it.
How Amplenote MCP Works
- 1 Install the integration in your AI workspace and provide your Amplenote Personal Access Token.
- 2 Your AI agent uses a natural language prompt (e.g., 'Find all tasks tagged #urgent').
- 3 The agent calls the relevant Amplenote tool, executes the action, and returns the structured data to you.
The bottom line is, your AI client interacts with Amplenote using standard function calls, treating your notes and tasks like a searchable database.
Who Is Amplenote MCP For?
Knowledge workers who manage research, project leads handling complex to-do lists, and developers needing to securely capture meeting minutes. If your job involves reading, writing, or organizing information across multiple silos, this is for you.
Uses the agent to search old research notes, synthesize key concepts, and generate an outline for a new article.
Asks the agent to check all incomplete tasks tagged with #urgent and drafts an immediate execution plan.
Dumps architecture concepts or meeting minutes directly into Amplenote via their IDE agent without losing focus.
What Changes When You Connect
- The agent searches your entire vault using
search_notes, finding content across notes and tasks instantly. You don't have to manually filter through old documents to find that one piece of data. - Never miss a deadline. You can ask the agent to check all incomplete items tagged with
#urgentand then uselist_tasksto view the full list. It keeps your to-do list live inside the chat. - Stop copy-pasting meeting notes. Use
create_noteto dump raw minutes or concepts directly into Amplenote, keeping your core work organized and searchable. - You always know your organizational boundaries. By calling
list_tags, the agent maps your entire tag hierarchy, so it knows exactly where the data lives. - Keep your documents current. If a key project detail changes, you run
update_noteto fix the content, and the agent knows the latest version. - Manage your workflow state. Use
get_taskorlist_tasksto check a specific item's status, or useupdate_taskto mark it complete, all from one prompt.
Real-World Use Cases
Synthesizing research for a paper
A technical writer needs to write an essay on quantum computing. They ask the agent to run search_notes for 'quantum' and 'ethics' across all notes. The agent returns the top 10 snippets, which the writer then uses to build a new outline using create_note.
Handling urgent project tasks
A project lead notices multiple tasks related to the Q3 launch. They ask the agent to list_tasks and filter for status 'pending' and tag '#urgent'. The agent then provides a list, allowing the lead to immediately update_task on the highest priority item.
Quickly capturing meeting minutes
A developer finishes a meeting. They prompt the agent to 'create a note titled Meeting Minutes' and dump the raw text. The agent uses create_note and automatically tags it for later retrieval.
Auditing project scope
A manager wants to know what notes and tasks are related to 'Project Phoenix'. They ask the agent to search_notes for the keyword and review the returned list to see if any critical actions were missed.
The Tradeoffs
Trying to manually copy notes
The user copies a paragraph from an old document, pastes it into the chat, and asks the agent to 'save this'. The agent can't know the source, and the context is lost.
→
Instead, ask the agent to get_note by UUID, or use search_notes to retrieve the original, structured content. This ensures the AI client works with the authoritative data source.
Forgetting the task status
The user completes a task and just mentions it in the chat, but nothing changes in the system of record. The task remains marked 'open'.
→
Use update_task and specify the task ID and set the status to 'complete'. This updates the official record, ensuring the task list is accurate.
Ignoring tags for organization
The user dumps unstructured text into a note, making it hard to find months later, because there's no way to filter it.
→
First, use list_tags to see the available organization categories. Then, when creating or updating, ask the agent to apply the appropriate tag (e.g., #project/finance).
When It Fits, When It Doesn't
Use this if you need your AI agent to act like a true personal assistant that lives inside your knowledge base. Specifically, if your workflow requires the agent to read historical notes (get_note) or manage actionable items (list_tasks), this server is essential. Don't use it if you just need a simple text generation tool; the server's job is state management and retrieval. If you only need to write a quick memo without tracking actions, a simple text editor is fine. But if you need to link a memo to a task, or search across notes and tasks simultaneously, you need Amplenote.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amplenote. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking research and to-dos across disconnected documents is a nightmare.
Today, if you need to find a specific idea, you open your notes app, search by keyword. You find the note, but you have to manually copy the relevant text into a second document. Then, if that note contains a task, you have to switch to your separate task manager, find the task, and update its status there. It's three different screens, three copy-pastes, and a chance to lose context.
With the Amplenote MCP Server, you ask your agent to search for 'Q3 budget tasks' using `search_notes`. The agent pulls the context from the note and the task status simultaneously. It delivers the answer in the chat, and you can tell it to `update_task` right there. It keeps the entire process in one window.
Amplenote MCP Server: Write and manage ideas from your chat.
You no longer have to open the full Amplenote app to capture a quick thought or update a deadline. You simply prompt the agent to 'create a note titled...' or 'add a task for John.' The agent runs `create_note` or `create_task` and handles the saving and tagging for you.
It's all about keeping the flow. You talk to your agent, and the agent talks to Amplenote. The documentation is now a live, interactive part of your conversation.
Common Questions About Amplenote MCP
How do I search my notes using the Amplenote MCP Server? +
Use the search_notes tool. This runs a full-text search across all your notes and tasks using keywords, bringing the results right into the chat window for review.
Can I create a new task using the Amplenote MCP Server? +
Yes, you can use the create_task tool. You simply prompt the agent with the task details, and it records it with priority and due dates in Amplenote.
What is the best way to get the content of one note using the Amplenote MCP Server? +
Use the get_note tool and provide the note's UUID. This retrieves the full, canonical content and all associated metadata for that specific note.
Does the Amplenote MCP Server track my organizational tags? +
Yes, the list_tags tool reads and analyzes your entire tag hierarchy, ensuring the agent knows your full organizational map.
How do I update a note using the Amplenote MCP Server? +
Use the update_note tool. You provide the note's UUID and the new content or title, and the agent saves the changes directly.
How do I manage tasks and notes using the `list_tasks` tool in the Amplenote MCP Server? +
The list_tasks tool retrieves all tasks across your entire Amplenote workspace. You get a list showing the task content, completion status, due dates, and which note it belongs to for a full overview.
What is the `create_note` tool for in the Amplenote MCP Server? +
The create_note tool lets you make new notes directly within your AI agent. You just need to provide a title and the Markdown body content for the new note.
How does the Amplenote MCP Server handle my data security? +
The connection requires your secure Amplenote Personal Access Token. Your AI client uses this token to perform actions, keeping your knowledge base contained within your own Amplenote workspace.
Can the agent interact with specific individual tasks within my notes? +
Yes. Amplenote's integration treats tasks as distinct manageable objects. You can not only list the pending items inside a note but also ask the agent to complete them, update their content, or inject an entirely new to-do row directly inside.
How does searching work across hundreds of deeply tagged notes? +
The integration utilizes Amplenote's robust search protocol. You simply tell the agent to 'find notes containing strategy tagged with #work/2026', and it will parse your complex nested structures efficiently without blindly guessing.
Can I trust the AI agent to update existing notes without wiping the rest of the text? +
Absolutely. Under the hood, the integration exposes granular update capabilities where the agent carefully dictates new structural alterations. It will append or replace specific regions accurately without overwriting unrelated brainstorming details.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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