raindropio-mcp 0.2.1

Unofficial MCP Server for the Raindrop.io API

Raindrop.io MCP Server

FastMCP-based Model Context Protocol server that exposes the Raindrop.io API to AI assistants. The server focuses on rich bookmark, collection, tag, highlights, filters, batch operations, and account operations while following the latest Raindrop REST documentation.

Key Capabilities

• Modern Raindrop API coverage – typed models for collections, bookmarks, tags, highlights/annotations, account profile, and cross-collection search.
• Batch operations – tools for moving, deleting, updating, tagging, and untagging multiple bookmarks at once.
• Advanced filtering – tools for applying complex filters to search and organize bookmarks.
• Import/Export – functionality to import bookmarks from external sources and export them in various formats.
• FastMCP tooling – tools registered with rich metadata so assistants can browse, filter, create, update, and delete Raindrop entities in natural flows.
• Typed configuration – RaindropSettings validates environment variables and exposes toggles for stdio or streamable HTTP transports.
• Reusable HTTP client – retry-aware, rate-limit friendly RaindropClient with explicit error mapping and pagination helpers.
• Tested implementation – pytest suite covering the client, tools, and entrypoints with coverage guardrails (≥80%).

Getting Started

Prerequisites

• Python 3.13 (managed by uv)
• A Raindrop.io personal access token

Installation

# clone and install dependencies
git clone https://github.com/lesleslie/raindropio-mcp.git
cd raindropio-mcp
uv sync

Configuration

Set the RAINDROP_TOKEN environment variable before launching the server. You can export the value or place it inside a .env file next to the project root.

export RAINDROP_TOKEN="your-raindrop-token"

Optional environment variables (all prefixed with RAINDROP_):

Variable	Default	Description
RAINDROP_USER_AGENT	raindropio-mcp/0.1.0	HTTP user agent header
RAINDROP_REQUEST_TIMEOUT	30.0	Seconds before an HTTP request times out
RAINDROP_MAX_CONNECTIONS	10	Maximum concurrent HTTP connections
RAINDROP_ENABLE_HTTP_TRANSPORT	false	Enable streamable HTTP transport
RAINDROP_HTTP_HOST	127.0.0.1	HTTP bind host when enabled
RAINDROP_HTTP_PORT	3034	HTTP port when enabled
RAINDROP_HTTP_PATH	/mcp	HTTP path for the MCP endpoint

Running the Server

# stdio (default)
uv run python -m raindropio_mcp

# or via the console script
uv run raindropio-mcp

# HTTP mode
uv run python -m raindropio_mcp --http --http-port 3034

example.mcp.json and example.mcp.dev.json demonstrate how to wire the server into MCP-enabled clients such as Claude Desktop or PowerShell integrations.

Available Tools

All tools are declared in raindropio_mcp/tools and registered automatically by register_all_tools.

Category	Tool	Description
Collections	list_collections	Fetch every collection visible to the token
	get_collection	Load metadata for a specific collection
	create_collection	Create a new collection/folder
	update_collection	Update title, description, or appearance
	delete_collection	Remove a collection (items move to Inbox)
Bookmarks	list_bookmarks	List bookmarks inside a collection with paging/search
	search_bookmarks	Full-text search across all collections
	get_bookmark	Retrieve a bookmark by id
	create_bookmark	Add a bookmark to a collection
	update_bookmark	Edit bookmark metadata or move between collections
	delete_bookmark	Delete a bookmark
Highlights	list_highlights	List all highlights for a specific bookmark
	get_highlight	Fetch a single highlight by its ID
	create_highlight	Create a new highlight for a bookmark
	update_highlight	Update an existing highlight
	delete_highlight	Delete a highlight by its ID
Batch	batch_move_bookmarks	Move multiple bookmarks to a different collection
	batch_delete_bookmarks	Delete multiple bookmarks
	batch_update_bookmarks	Update multiple bookmarks with the same changes
	batch_tag_bookmarks	Add tags to multiple bookmarks
	batch_untag_bookmarks	Remove tags from multiple bookmarks
Filters	apply_filters	Apply various filters to search and organize bookmarks across all collections
	get_filtered_bookmarks_by_collection	Apply filters to bookmarks within a specific collection
Import/Export	import_bookmarks	Import bookmarks from an external source into Raindrop.io
	export_bookmarks	Export bookmarks from Raindrop.io in a specified format
Tags	list_tags	Fetch tag usage counts
	rename_tag	Rename a tag globally
	delete_tag	Remove a tag across all bookmarks
Account	get_account_profile	Return the authenticated account profile
System	ping	Lightweight heartbeat including timestamp

Each tool returns JSON-serialisable payloads closely matching the official API shapes so downstream agents can consume data without additional parsing.

Observability & Shutdown

Logging defaults to structured JSON. Set RAINDROP_OBSERVABILITY_STRUCTURED_LOGGING=false (or override via .env) to switch to classic text formatting.

The FastMCP app registers a shutdown hook that gracefully closes the shared RaindropClient, ensuring HTTP connection pools are released when the server terminates.

Development Workflow

# lint + type-check + tests + security
uv run crackerjack

# individual tasks
uv run ruff check --fix
uv run mypy .
uv run pytest --cov=. --cov-report=term-missing

Test fixtures live in tests/ and automatically inject RAINDROP_TOKEN so unit execution never reaches the live API.

Roadmap

• Add optional caching middleware for high-volume assistant workflows
• Implement sharing functionality when Raindrop exposes those endpoints
• Enhance filter capabilities with additional options

Contributions and feature suggestions are welcome via issues or pull requests.