Evernote MCP. Manage your entire knowledge base with natural conversation.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
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Evernote MCP Server lets your AI agent manage all your personal notes. You can create new notes, list your notebooks, search content across all tags, and pull detailed metadata for specific notes.
It keeps your entire knowledge base organized and searchable, right inside your AI workflow.
What your AI agents can do
Create note
Creates a new note in a specified Evernote notebook, syncing it immediately across all your devices.
Create notebook
Creates a new Evernote notebook and returns its unique ID and metadata.
Get note
Retrieves the full content and metadata of a single Evernote note using its unique ID.
Your agent runs powerful queries across all notebooks, finding notes by keywords, tags, or creation dates.
Your agent provisions a new note in a specified notebook, and the content syncs immediately across all your devices.
Your agent lists all available notebooks and fetches detailed metadata about specific notebooks in your workspace.
Your agent pulls the complete content and metadata for a single note using its GUID.
Your agent lists all defined tags and manages nested tag hierarchies to filter and organize your notes.
Your agent retrieves your authenticated profile data, including your account tier and current quota usage.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
019d7593create note
Creates a new note in a specified Evernote notebook, syncing it immediately across all your devices.
019d7593create notebook
Creates a new Evernote notebook and returns its unique ID and metadata.
019d7593get note
Retrieves the full content and metadata of a single Evernote note using its unique ID.
019d7593get notebook
Fetches detailed metadata for a specific Evernote notebook using its unique ID.
019d7593get user
Gets the profile information for the currently connected Evernote user.
019d7593list notebooks
Retrieves a list of all notebooks in your connected Evernote account.
019d7593list notes
Lists up to 50 notes inside a specific notebook ID.
019d7593list tags
Retrieves all tags defined across your entire Evernote account.
019d7593search notes
Searches across all notes using Evernote's advanced query syntax (keywords, date filters, tags).
019d7593update note
Updates the title and/or content of an existing note, triggering a sync.
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 Evernote, 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
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- Every connection is secured and compliant automatically
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Evernote gives your AI agent total control over your personal knowledge base. You'll use this server to manage notes, notebooks, and tags right within your AI workflow. Your agent can run powerful queries across all your notebooks, finding notes by keywords, tags, or creation dates using advanced search syntax. Your agent can create a new note in a specified notebook, and the content syncs immediately across all your devices. Your agent lists all available notebooks, and you can fetch detailed metadata for a specific notebook using its unique ID.
If you need to check the full content and metadata for a single note, your agent retrieves it using the note's unique ID. You can also list all defined tags across your account and manage the nested tag hierarchy to filter your notes. You'll get your authenticated profile data, including your account tier and current quota usage, by asking your agent to get your user profile.
You can update an existing note's title or content, and that change syncs instantly. Your agent also lists up to 50 notes inside a specific notebook ID. Finally, your agent can create a new notebook and returns its unique ID and metadata.
How Evernote MCP Works
- 1 Subscribe to the server and enter your Evernote Developer Token (you find this in your Evernote Account Settings > Developer Token).
- 2 Tell your AI agent what you need: 'Find notes tagged 'Q3 Report' created last month.'
- 3 The agent calls the appropriate tool, and you get the structured data—like note lists or notebook metadata—back into your chat.
The bottom line is you manage your personal knowledge base using natural language, without opening the Evernote app.
Who Is Evernote MCP For?
Anyone who treats their digital life like a library needs this. Knowledge workers, researchers, and project managers spend too much time jumping between apps just to find one piece of context. This server lets you run complex queries and manage your entire personal archive from a single conversation.
Runs complex searches across years of research notes and pulls metadata to structure a literature review.
Creates drafts, updates notes, and manages tag hierarchies for documentation without opening the desktop app.
Audits notebook stacks, lists note counts, and tracks team contributions by asking the agent to summarize the workspace.
What Changes When You Connect
- Find specific info instantly. Instead of opening the app and filtering manually, just ask the agent to run
search_notesusing keywords, tags, or creation dates. It finds what you need immediately. - Control your data flow. Need to update a draft? Use
update_noteto change content or title and watch it sync across all your devices. No manual copy-pasting required. - Build your archive structure. Use
list_notebooksandcreate_notebookto manage your workspace hierarchy directly from your chat, treating your notes like code modules. - Deep dive into single notes. When you need the full context of one item,
get_notepulls the ENML content and metadata, giving you everything in one structured response. - Stay organized with tags. Use
list_tagsto see every tag you've used, and the agent helps you filter your notes by specific tag hierarchies. - Know your limits.
get_userlets you check your account quota and profile info, so you never hit a service limit unexpectedly.
Real-World Use Cases
Finding a specific research paper detail
A scientist needs to find a specific piece of data from a paper tagged 'Quantum Physics' and created last year. They ask the agent to run search_notes with the full query syntax. The agent returns a list of matching notes and metadata, allowing the scientist to grab the GUID and pull the full content using get_note.
Structuring a new project archive
A project manager starts a new initiative. Instead of creating folders in the app, they ask the agent to create_notebook for the project. Then, they use list_notebooks to verify the new structure, and start adding initial notes using create_note.
Updating an old meeting summary
A team member finds an old meeting note that needs correcting. They use get_note to retrieve the current content, edit it locally, and then ask the agent to update_note with the revised text, ensuring the change syncs everywhere.
Auditing the knowledge base structure
A developer needs to see the full scope of their knowledge base. They use list_notebooks to see the top-level structure, then list_tags to understand the categorization, and finally get_user to check the account's current capacity.
The Tradeoffs
Trying to search by partial keyword
Asking the agent to 'Find notes about recipes' and hoping it finds everything. The agent might miss notes if the query isn't specific enough.
→
Don't just ask for keywords. Use search_notes and explicitly include required tags or date ranges in your query syntax. For example, 'Find notes tagged 'Recipe' AND created after 2023-01-01'.
Forgetting to sync changes
Manually updating a note's text in a client and thinking the change is saved. The change might only exist locally and not in Evernote.
→
Always use the update_note tool. This triggers the necessary sync and ensures the change is recorded in the main Evernote database.
Relying on the app UI for structure
Trying to guess which notebook holds a note, leading to multiple manual clicks and context switching.
→
Start by calling list_notebooks to see your full workspace structure. Then, use list_notes on the specific notebook to narrow down your search scope.
When It Fits, When It Doesn't
Use this if your primary workflow involves finding, organizing, or drafting content that lives inside Evernote. You need to manage structured knowledge—notes, notebooks, tags—from a chat interface. Use it when you need to execute a complex, multi-step retrieval process (e.g., 'Find all notes tagged X, but only those in Notebook Y, that mention Z').
Don't use this if you just need a simple text editor or if your knowledge is stored in a different system (like a CRM or Google Docs). For those cases, you need a different type of connector. If you only need to read the content of a single note and don't need to manage its metadata or tags, you could use a simpler, read-only API wrapper instead.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Evernote. 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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding buried notes shouldn't feel like a database audit.
Today, finding a single piece of research requires opening the Evernote app, navigating through notebooks, filtering by date, and manually checking tags. You often end up in a cycle of clicking 'Search' and adjusting filters until you find the right GUID, losing context with every click.
With the Evernote MCP Server, you just ask. The agent handles the navigation. You tell it: 'Find all notes tagged 'Q3 Report' in the 'Research' notebook.' It executes the `search_notes` tool, returns the results, and you get the information without touching the app interface.
Evernote MCP Server: Control your entire knowledge base.
Manual processes used to require separate steps: first, listing notebooks (`list_notebooks`); second, listing notes within them (`list_notes`); and finally, retrieving the content (`get_note`). This is slow, and you always lose track of which ID belongs to what.
Now, you treat it as one task. You ask the agent to 'Get me the metadata for the 'Project Alpha' notebook and list the top 5 notes.' It handles the sequential calls and gives you a structured answer immediately. It's seamless.
Common Questions About Evernote MCP
How do I use the `search_notes` tool with tags? +
You use advanced query syntax directly in your prompt. Include the tag name and the search term (e.g., 'Find notes containing 'budget' AND tagged 'Finance''). The agent runs search_notes and returns the matching metadata.
Does `get_note` give me the content or just the metadata? +
get_note returns both the full content and the metadata. It delivers the content in Evernote Markup Language (ENML), which preserves formatting.
What if I want to add a new note? Do I use `create_note`? +
Yes, use create_note. Just tell the agent the title, the notebook name, and the plain text content. It handles the creation and sync process for you.
Can I check my account quota using `get_user`? +
Yes, get_user fetches your profile details, including your account tier and real-time quota usage. This is useful for monitoring service limits.
Is there a tool to find all my tags? Do I use `list_tags`? +
Yes, use list_tags. This tool retrieves all defined tags across your entire account, letting you see your full organization scope.
How do I manage my workspace structure using `list_notebooks` and `get_notebook`? +
You use list_notebooks first to see all available notebooks. Then, you can use get_notebook with the specific GUID to fetch detailed metadata, like note counts and stack assignments. This helps you map out your entire organizational topology.
Can I update an existing note's content using the `update_note` tool? +
Yes, update_note modifies the title and content of a note you already have. Crucially, running this tool triggers a sync and increments the updateSequenceNum, ensuring the change is recorded across all your devices.
What information does `get_user` provide about my Evernote account? +
get_user pulls your profile information. It provides the account tier, service level, and real-time quota usage, so you always know your current system limits.
Can my agent search for notes with specific tags in Evernote? +
Yes. Use the 'search_notes' tool. You can use Evernote's query syntax like 'tag:work' or 'tag:ideas' to filter results. The agent executes the structural match and returns matching note metadata.
How do I create a new note in a specific notebook via chat? +
Use the 'create_note' tool. Provide the 'notebook_id' (GUID), a title, and the content. The note will be created and synced across all your Evernote clients immediately.
Can I check my monthly upload quota through the agent? +
Absolutely. Use the 'get_user' tool. Your agent will fetch authenticated profile information, including your current quota usage and service tier, to help you stay within system limits.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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