How to Use the Evernote MCP in OpenAI Agents SDK

Q: How do I install this Evernote MCP Server for the OpenAI Agents SDK?

Run pip install openai-agents. You pass the server URL to MCPServerStreamableHttp and hand it to your Agent constructor. Set cacheToolsList=True so it discovers the tools faster.

Q: Can OpenAI Agents SDK read my formatted Evernote tables?

Yes. When the agent calls getnote, the server returns the raw Evernote Markup Language (ENML). Your agent parses that markup to understand tables and text formatting.

Q: Will this MCP server hit Evernote API rate limits with OpenAI Agents SDK?

It might if you run tight loops. Use the getuser tool to check your account quotas before running massive batch jobs. OpenAI guardrails can help throttle these requests.

Connect Evernote to your OpenAI Agents SDK system. Give your production agents persistent memory and note management.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Evernote MCP to OpenAI Agents SDK

Create your Vinkius account to connect Evernote to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Evernote with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Give OpenAI Agents SDK a permanent memory core.

The `create_note` tool writes data directly to Evernote, making this MCP server a literal memory bank for your agents. You don't have to build a vector database from scratch. Your agent drafts a summary, creates a note, and it syncs immediately across all your devices. The `get_user` tool pulls your account quotas so one specialized agent can generate a report, while another uses `get_note` to read the exact ENML content. Handoffs get much easier when agents share a notebook. Everything gets tracked natively in your OpenAI dashboard.

Search and filter existing knowledge.

The `search_notes` tool lets your agent query your entire Evernote history using native query syntax. If your agent needs context on a past project, it just runs a search and pulls the matching metadata without guessing where the file lives. The `list_tags` tool filters specific topics, and `list_notebooks` maps out exactly where you keep your files. Once the agent finds the right spot, it uses `list_notes` to pull up to 50 records at a time.

Edit and organize workspaces autonomously.

The `create_notebook` tool spins up a new folder for a specific task, returning the fresh GUID instantly. Your agent can restructure a messy workspace without you lifting a finger. The `update_note` tool modifies the title or body of an existing file. This increments the updateSequenceNum and forces a sync across your devices. Your guardrails ensure the agent only touches the notebooks you explicitly allow.

Setup guide

Set up Evernote MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Evernote tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Evernote tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Evernote tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Evernote Agent",
            instructions="You have access to Evernote tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Evernote now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Evernote MCP in OpenAI Agents SDK

Run `pip install openai-agents`. You pass the server URL to `MCPServerStreamableHttp` and hand it to your Agent constructor. Set `cacheToolsList=True` so it discovers the tools faster.

Yes. When the agent calls `get_note`, the server returns the raw Evernote Markup Language (ENML). Your agent parses that markup to understand tables and text formatting.

It might if you run tight loops. Use the `get_user` tool to check your account quotas before running massive batch jobs. OpenAI guardrails can help throttle these requests.

Yes, unless your agent explicitly reads the current content first. Make sure your agent calls `get_note` to grab the current ENML, appends the new text, and then pushes the update.

The server only accesses the specific notes, ENML content, and tags you authorize via your developer token. Vinkius runs this connection in an ephemeral V8 Isolate sandbox, meaning your raw note data passes directly to your agent and vanishes from our memory the millisecond the sync finishes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript