productivity

Raindrop.io

by adeze

Easily manage and export bookmarks and favorites in Chrome with Raindrop.io. The top bookmark manager for collections, t

Integrates with Raindrop.io bookmarking service to provide direct access for managing collections, bookmarks, tags, highlights, and user data without leaving your conversation context.

github stars

128

Requires Raindrop.io API tokenMultiple transport options

best for

  • / Knowledge workers managing research links
  • / Content creators organizing reference materials
  • / Anyone with large bookmark collections

capabilities

  • / Search through saved bookmarks
  • / Create new bookmarks
  • / Retrieve bookmark collections
  • / Access authenticated Raindrop.io account

what it does

Connect to your Raindrop.io bookmarks to search, add, and organize saved links directly from your AI assistant.

about

Raindrop.io is a community-built MCP server published by adeze that provides AI assistants with tools and capabilities via the Model Context Protocol. Easily manage and export bookmarks and favorites in Chrome with Raindrop.io. The top bookmark manager for collections, t It is categorized under productivity.

how to install

You can install Raindrop.io in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Raindrop.io is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Raindrop.io MCP Server

smithery badge npm version Claude Desktop MCPB

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

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:

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-mcp

Manual 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

Support

📋 Recent Enhancements (v2.3.9)

Smart Organization & Hierarchy

  • AI Suggestions: New get_suggestions tool provides organizational advice using Raindrop's API and MCP Sampling.
  • Collection Tree: get_collection_tree tool provides a hierarchical view with full breadcrumb paths.
  • Bulk Move: Added move operation to bulk_edit_raindrops for efficient library organization.
  • Pagination Support: Standardized list_raindrops and bookmark_search with 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.

📋 Previous Enhancements (v2.3.3)

Advanced Cleanup & Library Audit

📋 Previous Enhancements (v2.3.2)

MCP Resource Links Implementation

  • Modern resource content following MCP SDK v1.25.3 best practices
  • Efficient 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} and mcp://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.

FAQ

What is the Raindrop.io MCP server?
Raindrop.io is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Raindrop.io?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Raindrop.io is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Raindrop.io against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Raindrop.io is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Raindrop.io reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Raindrop.io for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Raindrop.io surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Raindrop.io has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Raindrop.io benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Raindrop.io into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Raindrop.io is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.