raindrop-mcp-server

A Model Context Protocol (MCP) server implementation for Raindrop.io, exposing its API as a set of tools for AI agents and automated workflows.

Table of Contents

1. Quick Start
2. Installation
3. Configuration
4. Usage
5. Requirements
6. Troubleshooting
7. Contributing
8. License

Quick Start

1. Download the latest binary from GitHub Releases
2. Get API Token from Raindrop.io Settings → Integrations
3. Configure Claude Desktop (claude_desktop_config.json):

   {
     "mcpServers": {
       "raindrop": {
         "command": "/usr/local/bin/raindrop-mcp-server",
         "env": {
           "RAINDROP_ACCESS_TOKEN": "your_token_here"
         }
       }
     }
   }
   

4. Start using: Ask Claude to "Show me all my Raindrop collections"

Installation

Pre-built Binaries (Recommended)

Download from GitHub Releases:

Linux:

wget https://github.com/yamahigashi/raindrop-mcp-server-rs/releases/download/latest/raindrop-mcp-server-linux.tar.gz
tar -xzf raindrop-mcp-server-v0.1.0-linux.tar.gz
chmod +x raindrop-mcp-server-linux
sudo mv raindrop-mcp-server-linux /usr/local/bin/raindrop-mcp-server

Windows:

Invoke-WebRequest -Uri "https://github.com/yamahigashi/raindrop-mcp-server-rs/releases/download/v0.1.0/raindrop-mcp-server-v0.1.0-windows.zip" -OutFile "raindrop-mcp-server.zip"
Expand-Archive -Path "raindrop-mcp-server.zip" -DestinationPath "."
# Move raindrop-mcp-server-windows.exe to a directory in your PATH

From Source

git clone https://github.com/yamahigashi/raindrop-mcp-server-rs.git
cd raindrop-mcp-server-rs
cargo build --release
# Binary: ./target/release/raindrop-mcp-server

Configuration

1. Raindrop.io API Token

1. Log in to Raindrop.io
2. Go to Settings → Integrations
3. Create a new app or select an existing one
4. Generate an access token

2. MCP Client Setup

For Claude Desktop, edit claude_desktop_config.json:

{
  "mcpServers": {
    "raindrop": {
      "command": "/usr/local/bin/raindrop-mcp-server",
      "env": {
        "RAINDROP_ACCESS_TOKEN": "your_raindrop_access_token_here"
      }
    }
  }
}

For development, create .env file:

RAINDROP_ACCESS_TOKEN=your_raindrop_access_token_here
RUST_LOG=info

Usage

Once configured, the MCP server provides the following tools to AI assistants:

Collection Management

• get_collections - List all collections
• get_collection - Get a specific collection
• create_collection - Create a new collection
• update_collection - Update collection properties
• delete_collection - Delete a collection
• share_collection - Share a collection with others

Bookmark Operations

• get_bookmarks - Retrieve bookmarks with filtering
• get_bookmark - Get a specific bookmark
• create_bookmark - Create a new bookmark
• update_bookmark - Update bookmark properties
• delete_bookmark - Delete a bookmark
• search_bookmarks - Search bookmarks with advanced filters
• batch_update_bookmarks - Update multiple bookmarks at once
• batch_delete_bookmarks - Delete multiple bookmarks

Tag Management

• get_tags - List all tags or tags from a specific collection
• rename_tag - Rename a tag across all b

... View full README on GitHub