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raindrop-io-mcp-server

MCP.Pizza Chef: hiromitsusasaki

The raindrop-io-mcp-server is an MCP server integration that enables large language models (LLMs) to interact directly with Raindrop.io bookmarks. It supports creating new bookmarks, searching existing ones, and filtering bookmarks by tags, providing a structured and real-time interface for managing Raindrop.io data. Designed for Node.js 16+ environments, it requires a Raindrop.io account and API token for authentication. This server facilitates enhanced AI workflows by allowing models like GPT-4, Claude, and Gemini to access and manipulate bookmark data securely and efficiently through the Model Context Protocol.

Use This MCP server To

Create new bookmarks in Raindrop.io via LLM commands Search Raindrop.io bookmarks using natural language queries Filter bookmarks by tags for organized retrieval Integrate bookmark management into AI-powered workflows Enable LLMs to access personal bookmark collections securely

README

Raindrop.io MCP Server

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An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP).

Raindrop.io Server MCP server

Features

  • Create bookmarks
  • Search bookmarks
  • Filter by tags

Requirements

  • Node.js 16 or higher
  • Raindrop.io account and API token

Setup

Installing via Smithery

To install Raindrop.io Integration for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @hiromitsusasaki/raindrop-io-mcp-server --client claude

Manual Installation

  1. Clone the repository:
git clone https://github.com/hiromitsusasaki/raindrop-io-mcp-server
cd raindrop-io-mcp-server
  1. Install dependencies:
npm install
  1. Set up environment variables:
  • Create a .env file and set your Raindrop.io API token
RAINDROP_TOKEN=your_access_token_here
  1. Build:
npm run build

Using with Claude for Desktop

  1. Open Claude for Desktop configuration file:
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  1. Add the following configuration:
{
  "mcpServers": {
    "raindrop": {
      "command": "node",
      "args": ["PATH_TO_BUILD/index.js"],
      "env": {
        "RAINDROP_TOKEN": "your_access_token_here"
      }
    }
  }
}
  1. Restart Claude for Desktop

Available Tools

create-bookmark

Creates a new bookmark.

Parameters:

  • url: URL to bookmark (required)
  • title: Title for the bookmark (optional)
  • tags: Array of tags (optional)
  • collection: Collection ID (optional)

search-bookmarks

Searches through bookmarks.

Parameters:

  • query: Search query (required)
  • tags: Array of tags to filter by (optional)

Development

# Build for development
npm run build

# Start server
npm start

Security Notes

  • Always manage API tokens using environment variables
  • Set appropriate permissions for Claude for Desktop configuration files
  • Restrict unnecessary file access

Open Source

This is an open source MCP server that anyone can use and contribute to. The project is released under the MIT License.

Contributing

Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to help improve this project.

Related Links

raindrop-io-mcp-server FAQ

How do I authenticate the raindrop-io-mcp-server?
You need a Raindrop.io account and an API token to authenticate and enable the server to access your bookmarks.
What are the system requirements for running this MCP server?
It requires Node.js version 16 or higher to run properly.
Can I install the raindrop-io-mcp-server automatically?
Yes, you can install it via Smithery CLI with a single command for easy setup.
Does this server support filtering bookmarks by tags?
Yes, it allows filtering bookmarks by tags to help organize and retrieve specific bookmark sets.
Is the raindrop-io-mcp-server compatible with multiple LLM providers?
Yes, it works with various LLMs including OpenAI's GPT-4, Anthropic's Claude, and Google’s Gemini.
How do I manually install the raindrop-io-mcp-server?
You can clone the repository and follow the setup instructions provided in the GitHub readme.
Can the server create bookmarks through LLM interactions?
Yes, it supports creating new bookmarks directly via model commands.
Is the interaction with Raindrop.io bookmarks real-time?
Yes, the server provides real-time access and manipulation of bookmarks through MCP.