Bring Personal Knowledge Base
to LangChain
Create your Vinkius account to connect Evernote to LangChain and start using all 10 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Evernote MCP Server?
Connect your Evernote account to any AI agent and take full control of your personal knowledge management and note-taking workflows through natural conversation.
What you can do
- Note & Content Orchestration — Retrieve the full body and metadata of any note by GUID, including ENML body content and nested attachment attributes natively
- Semantic & Syntax Search — Execute powerful queries across all notebooks using Evernote's advanced syntax (keywords, tag filters, creation dates) to find information instantly
- Notebook Management — List all notebooks and retrieve detailed metadata including note counts and stack assignments to browse your workspace hierarchy
- Live Note Creation — Provision new notes inside specific notebooks by providing titles and plain-text or ENML content for immediate cross-device synchronization
- Categorical Tagging — Enumerate explicitly defined tags and manage nested tag hierarchies to filter and organize your personal database strictly
- Account & Quota Oversight — Fetch authenticated profile information including account tier, service level, and real-time quota usage to monitor system limits
- Metadata Auditing — Retrieve structural notebook representations and identify default status boundaries to manage your organizational topology flawlessly
How it works
- Subscribe to this server
- Enter your Evernote Developer Token (found in your Evernote Account Settings > Developer Token)
- Start managing your notes from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Knowledge Workers — search for research notes and organize meeting minutes using natural language
- Writers & Researchers — create and update drafts and manage tag hierarchies without opening the Evernote app
- Project Managers — audit notebook stacks and monitor team contribution counts through natural conversation
- Developers — test and debug Evernote ENML rendering and note synchronization logic in real-time
Built-in capabilities (10)
The note is immediately synced and available across all Evernote clients. Create a new note inside a specified Evernote notebook
Returns the newly created notebook GUID and metadata. Create a new Evernote notebook
The content is returned in Evernote Markup Language (ENML). Retrieve the full content and metadata of a single Evernote note by GUID
Fetch detailed metadata for a specific Evernote notebook by its GUID
Get profile information for the currently authenticated Evernote user
Use this to discover available notebooks before listing notes within them. Retrieve all Evernote notebooks for the authenticated account
Use en.get_note to fetch full content. List up to 50 notes inside a specific Evernote notebook
Useful for filtering and organizing notes. Retrieve all tags defined in the Evernote account
Returns matching note metadata. Search across all Evernote notes using Evernote's powerful query syntax
This triggers a sync and increments the updateSequenceNum. Update the title and/or content of an existing Evernote note
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Evernote through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Evernote MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Evernote queries for multi-turn workflows
Evernote in LangChain
Why run Evernote with Vinkius?
The Evernote connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 10 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Evernote using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Evernote and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Evernote to LangChain through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Evernote for LangChain
Every request between LangChain and Evernote is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
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.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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