Joplin MCP

Joplin MCP

Exposes a Joplin note collection as a tool set to MCP clients, running on Cloudflare Workers. It enables semantic search over indexed notes, notebook browsing, and creating/updating/deleting notes and notebooks via the Joplin Data API.

Category
Visit Server

README

Joplin MCP

An MCP server that exposes a Joplin note collection as a tool set, running as a stateful agent on Cloudflare Workers. Point an MCP client (Claude, etc.) at the deployed endpoint and it can browse notebooks and notes, and create/update/delete notes and notebooks directly against your own Joplin instance.

How it works

Every tool call goes straight to the Joplin Data API on your live instance — there's no index or cache in between.

MCP client ──HTTP/SSE──► Worker (/mcp) ──► JoplinMCP (Durable Object)
                                                  │
                                    JoplinClient ──► Joplin Data API

JoplinMCP is a McpAgent hosted on a Durable Object.

Tools

Tool Description
get_note Fetch a single note by ID — title, body, metadata
list_notebooks List all notebooks with IDs and names
list_notes List notes in a given notebook
create_note Create a note in a notebook
update_note Update a note's title, body, or notebook
delete_note Permanently delete a note
create_notebook Create a notebook, optionally nested
update_notebook Rename or move a notebook
delete_notebook Move a notebook (and its notes) to trash

Setup

npm install
wrangler secret put JOPLIN_API_TOKEN   # Joplin Data API token

Before deploying, set vars.JOPLIN_CLIENT_URL in wrangler.jsonc to the base URL of your Joplin Data API.

See CLAUDE.md for the full architecture and binding reference.

Development

npm run dev         # wrangler dev — local development with hot reload
npm run test        # vitest run
npm run typecheck   # tsc --noEmit

Deploy

npm run deploy

Or connect this repository to a Cloudflare Worker for git-based deploys. Either way, JOPLIN_API_TOKEN must be set as a Wrangler secret in the target environment — it is never stored in the repo.

Stack

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured