Raindrop.io MCP Server
# Raindrop.io MCP Server
[](https://smithery.ai/server/@hiromitsusasaki/raindrop-io-mcp-server)
An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP).
<a href="https://glama.ai/mcp/servers/@hiromitsusasaki/raindrop-io-mcp-server">
<img width="380" height="200" src="https://glama.ai/mcp/servers/@hiromitsusasaki/raindrop-io-mcp-server/badge" alt="Raindrop.io Server MCP server" />
</a>
## 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](https://smithery.ai/server/@hiromitsusasaki/raindrop-io-mcp-server):
```bash
npx -y @smithery/cli install @hiromitsusasaki/raindrop-io-mcp-server --client claude
```
### Manual Installation
1. Clone the repository:
```bash
git clone https://github.com/hiromitsusasaki/raindrop-io-mcp-server
cd raindrop-io-mcp-server
```
2. Install dependencies:
```bash
npm install
```
3. Set up environment variables:
- Create a `.env` file and set your Raindrop.io API token
```
RAINDROP_TOKEN=your_access_token_here
```
4. Build:
```bash
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`
2. Add the following configuration:
```json
{
"mcpServers": {
"raindrop": {
"command": "node",
"args": ["PATH_TO_BUILD/index.js"],
"env": {
"RAINDROP_TOKEN": "your_access_token_here"
}
}
}
}
```
3. 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
```bash
# 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
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [Raindrop.io API Documentation](https://developer.raindrop.io/)TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: create-bookmark for adding new bookmarks, list-collections for viewing collections, and search-bookmarks for finding existing bookmarks. There is no overlap in functionality, making it easy for an agent to select the correct tool without confusion.
All tool names follow a consistent verb_noun pattern (create-bookmark, list-collections, search-bookmarks) with hyphens used uniformly. This predictable naming scheme enhances readability and usability for agents.
With only 3 tools, the server feels thin for a bookmark management domain, lacking essential operations like update, delete, or get specific bookmarks/collections. While the tools cover basic actions, the count is borderline low for comprehensive functionality.
The tool surface has significant gaps for a bookmark manager: no update-bookmark, delete-bookmark, get-bookmark, or get-collection tools, and no lifecycle management for collections. This incomplete coverage will likely cause agent failures in common workflows like editing or removing bookmarks.