This server provides an interface to manage Raindrop.io bookmarking service via the Model Context Protocol (MCP), allowing you to:
Bookmark Management: Create, read, update, and delete bookmarks individually or in batches, with filtering by tags, domain, type, creation date, and importance
Collection Operations: Create, manage, reorder, merge, share, and remove empty collections
Tag System: List, rename, merge, and delete tags
Highlights: Access and manage text highlights from saved content
User Data: Retrieve account information and statistics
Reminders: Set and delete reminders for specific bookmarks
Import/Export: Transfer bookmarks in formats like CSV, HTML, and PDF
Trash Management: Empty trash permanently
Advanced Search: Filter and sort bookmarks with pagination
Real-time Updates: Receive streaming updates via Server-Sent Events
Used for making HTTP requests to the Raindrop.io API
Can be used for installing dependencies and running the Raindrop.io MCP server
Used for environment variable configuration in the Raindrop.io MCP server
Required to run the Raindrop.io MCP server (v18 or later recommended)
Allows installing and running the Raindrop.io MCP server via npx command
Used for implementing the Raindrop.io MCP server with strong typing for better maintainability
Used for schema validation of API parameters and responses in the Raindrop.io MCP server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Raindrop.iofind my bookmarks about machine learning from last week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Raindrop.io MCP Server
Connect Raindrop.io to your AI assistant with a simple MCP server. Use it to organize, search, and manage bookmarks with natural language.
What it can do
Create, update, and delete collections and bookmarks
Search bookmarks by tags, domain, type, date, and more
Manage tags (list, rename, merge, delete)
Read highlights from bookmarks
Bulk edit bookmarks in a collection
Import/export bookmarks and manage trash
Related MCP server: Weather Service MCP Server
Tools
diagnostics - Server diagnostic information and library health metrics
collection_list - List all collections as a flat list
get_collection_tree - Hierarchical view of collections with full breadcrumb paths
collection_manage - Create, update, or delete collections
bookmark_search - Advanced search with filters, tags, and pagination
bookmark_manage - Create, update, or delete bookmarks
get_raindrop - Fetch a single bookmark by ID
list_raindrops - List bookmarks for a collection with pagination
get_suggestions - AI-powered organization advice (tags/collections) for a URL or bookmark
bulk_edit_raindrops - Bulk update, move, or remove bookmarks in a specific collection
tag_manage - Rename, merge, or delete tags
highlight_manage - Create, update, or delete highlights
library_audit - Scan library for broken links, duplicates, and untagged items
empty_trash - Permanently empty the trash (requires confirmation)
cleanup_collections - Remove empty collections (requires confirmation)
Install
Claude Desktop (MCPB)
Download the latest raindrop-mcp.mcpb from the GitHub Release and add it to Claude Desktop:
Releases: https://github.com/adeze/raindrop-mcp/releases
In Claude Desktop, add the bundle and set this environment variable:
RAINDROP_ACCESS_TOKEN (from your Raindrop.io integrations settings)
NPX (CLI)
Set your API token as an environment variable and run:
export RAINDROP_ACCESS_TOKEN=YOUR_RAINDROP_ACCESS_TOKEN
npx @adeze/raindrop-mcpManual MCP config (mcp.json)
Add this to your MCP client configuration:
{
"servers": {
"raindrop": {
"type": "stdio",
"command": "npx",
"args": ["@adeze/raindrop-mcp@latest"],
"env": {
"RAINDROP_ACCESS_TOKEN": "YOUR_RAINDROP_ACCESS_TOKEN"
}
}
}
}Requirements
A Raindrop.io account
A Raindrop.io API Access Token: https://app.raindrop.io/settings/integrations
Support
Issues: https://github.com/adeze/raindrop-mcp/issues
π Recent Enhancements (v2.3.9)
Smart Organization & Hierarchy
AI Suggestions: New
get_suggestionstool provides organizational advice using Raindrop's API and MCP Sampling.Collection Tree:
get_collection_treetool provides a hierarchical view with full breadcrumb paths.Bulk Move: Added
moveoperation tobulk_edit_raindropsfor efficient library organization.Pagination Support: Standardized
list_raindropsandbookmark_searchwith pagination for large libraries.
Safety & Quality
Confirmation Logic: Destructive tools (
empty_trash,cleanup_collections) now require explicit confirmation.Standardized Naming: All tools now use consistent snake_case naming conventions.
CI/CD Pipeline: Enhanced GitHub Actions with automated linting, type-checking, and cross-transport tests.
Code Quality: Established ESLint and Prettier configurations for maintainable development.
π Previous Enhancements (v2.3.3)
Advanced Cleanup & Library Audit
π Previous Enhancements (v2.3.2)
MCP Resource Links Implementation
Modern
resourcecontent following MCP SDK v1.25.3 best practicesEfficient data access: tools return lightweight links instead of full payloads
Better performance: clients fetch full bookmark/collection data only when needed
Seamless integration with dynamic resource system (
mcp://raindrop/{id})
SDK & API Updates
Updated to MCP SDK v1.25.3
Modern tool registration with improved descriptions
Fixed API endpoints and path parameters
All core tools fully functional
Tool Optimization
Resource-efficient responses for bookmark/collection lists
Dynamic resource access via
mcp://collection/{id}andmcp://raindrop/{id}Better client UX with lighter list payloads
Full MCP compliance with official SDK patterns
Service Layer Improvements
Reduced code through extracted common helpers
Consistent error handling and response processing
Enhanced type safety with generic handlers
Centralized endpoint building
Testing Improvements
Stronger end-to-end coverage for MCP tool execution
Expanded integration tests for real-world client flows
MCP 2.0 Preparation (Bulk Ops)
Laying groundwork for MCP 2.0 bulk-operation workflows and tooling
OAuth (Coming Soon)
OAuth-based auth flow to simplify setup without manual tokens
Note
Apologies to anyone affected by the last couple of builds. Thank you for the patience and reports.
License
This project is licensed under the MIT License - see the LICENSE file for details.