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.

Evernote MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Evernote
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Evernote as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="evernote_agent",
    instruction=(
        "You help users interact with Evernote "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About 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.

Google ADK natively supports Evernote as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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

The Evernote MCP Server exposes 10 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Evernote to Google ADK via MCP

Follow these steps to integrate the Evernote MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 10 tools from Evernote via MCP

Why Use Google ADK with the Evernote MCP Server

Google ADK provides unique advantages when paired with Evernote through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Evernote

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine Evernote tools with BigQuery, Vertex AI, and Cloud Functions

Evernote + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Evernote MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Evernote and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Evernote tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Evernote regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Evernote

Evernote MCP Tools for Google ADK (10)

These 10 tools become available when you connect Evernote to Google ADK via MCP:

create_note

The note is immediately synced and available across all Evernote clients. Create a new note inside a specified Evernote notebook

create_notebook

Returns the newly created notebook GUID and metadata. Create a new Evernote notebook

get_note

The content is returned in Evernote Markup Language (ENML). Retrieve the full content and metadata of a single Evernote note by GUID

get_notebook

Fetch detailed metadata for a specific Evernote notebook by its GUID

get_user

Get profile information for the currently authenticated Evernote user

list_notebooks

Use this to discover available notebooks before listing notes within them. Retrieve all Evernote notebooks for the authenticated account

list_notes

Use en.get_note to fetch full content. List up to 50 notes inside a specific Evernote notebook

list_tags

Useful for filtering and organizing notes. Retrieve all tags defined in the Evernote account

search_notes

Returns matching note metadata. Search across all Evernote notes using Evernote's powerful query syntax

update_note

This triggers a sync and increments the updateSequenceNum. Update the title and/or content of an existing Evernote note

Example Prompts for Evernote in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Evernote immediately.

"Create a note in 'Work' notebook with title 'Meeting Actions' and content 'Follow up with team.'"

"Search for notes containing 'recipe' and tagged 'favorite'"

"List all my notebooks and their note counts"

Troubleshooting Evernote MCP Server with Google ADK

Common issues when connecting Evernote to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Evernote + Google ADK FAQ

Common questions about integrating Evernote MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.