rdrop for Raindrop.io

Name: rdrop for Raindrop.io
Author: KingPsychopath

by KingPsychopathversion 0.2.1i★ –iRuns on your computer

Registry nameio.github.KingPsychopath/raindrop-cli

Install

Overview

Description from the maker (original English)

Search Raindrop.io bookmarks and review tag and collection plans. Read-only MCP by default.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: RAINDROP_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: RAINDROP_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "raindrop-cli": {
      "command": "npx",
      "args": [
        "-y",
        "@machineyearn/raindrop-cli",
        "mcp",
        "serve"
      ],
      "env": {
        "RAINDROP_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add raindrop-cli --env RAINDROP_TOKEN=your-value -- npx -y @machineyearn/raindrop-cli mcp serve

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "raindrop-cli": {
      "command": "npx",
      "args": [
        "-y",
        "@machineyearn/raindrop-cli",
        "mcp",
        "serve"
      ],
      "env": {
        "RAINDROP_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "raindrop-cli": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@machineyearn/raindrop-cli",
        "mcp",
        "serve"
      ],
      "env": {
        "RAINDROP_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

RAINDROP_TOKEN secret env
Raindrop.io API token. Alternatively configure the private rdrop env/token file; see setup.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account KingPsychopath, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7247 servers in this category
Published to the registry more recently than 58% of the other 7247 servers in this category
Basic checks equal to or better than 100% of the other 7247 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is rdrop for Raindrop.io safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: RAINDROP_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 27 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

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Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

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Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

rdrop for Raindrop.io

Find, review and organize your saved links. Keep your tags. Bring your own AI.

Turn a growing Raindrop.io library into something easier to use. Search saved links, inspect collections, find cleanup opportunities and review suggestions before making changes. Use it from your terminal or let your favorite agent do the reading and planning.

A Raindrop.io CLI, MCP server and reviewed bookmark organizer from Machineyearn, built as an independent integration.

Your organization stays yours. Start with the tags and collections you already created; preserve existing tags when applying a plan.
Changes you can inspect. See exact bookmarks, proposed tags and destinations, then dry-run the plan before applying it.
AI that fits your workflow. Connect Codex or Claude, use a hosted tool-capable model, or run local Qwen and Laya.
A useful CLI without AI. Search, edit, export, manage highlights and collections, and build shell pipelines.

Get started

1. Install

brew install machineyearningengineer/tap/rdrop

Or Node 22+, with optional dependencies enabled:

npm install --global @machineyearn/raindrop-cli@0.2.1 rdrop version

Prefer no global install? Use npx --yes @machineyearn/raindrop-cli@0.2.1 COMMAND. Native downloads cover macOS, Linux and Windows on Intel/AMD and ARM. Builds and checksums.

2. Connect Raindrop

Create a token in your Raindrop integration settings. Add it to the private file ~/.config/rdrop/env:

RAINDROP_TOKEN=your_token_here

Give the directory permissions 700 and the file 600, then run rdrop doctor. Keep the token out of chat and Git. Setup and troubleshooting.

3. Ask your agent

Copy this into Codex, Claude or your preferred coding agent. It can help with setup too:

Set up https://github.com/machineyearningengineer/raindrop-cli so you can help

manage my Raindrop library. Use its plugin/MCP when available, otherwise use the CLI. Check installation and authentication; have me add the token privately. Use the existing model and configured services first.

Start with a cleanup report and a small sample. Use my existing tags and collections. Choose useful tools for search, content, classification and planning; connect extra model providers, Executor or ACP only if needed. Show the exact proposed changes and a dry-run. Preserve my tags and notes, flag uncertain suggestions, and apply only the exact plan I approve.

Connect an agent, or start in your shell with rdrop collections --tree, rdrop search 'type:article #go' --json and rdrop cleanup report --json.

Choose your workflow

You want to…	Start here
Find links, manage collections or export your library	Shell commands
Use Codex, Claude or another MCP client	Client setup and plugins
Ask a model to inspect your library and propose changes	Run a model directly
Use Raindrop's semantic search and AI-assisted reads	Official MCP tools
Classify selected bookmarks with Jev, Laya or Clef	Decision providers
Run portable Raindrop tools in Executor	Executor setup

Organize with a plan

Begin with a report and select the exact bookmarks you want to review:

rdrop cleanup report --json > cleanup-report.json

rdrop context --ids 101,102 > library-context.json jq 'del(.snapshots)' library-context.json > model-context.json

The model view contains your existing tag names, collection paths and bookmark metadata. Keep the original context private: its snapshots are used to detect edits before applying. Ask any model or rule engine for the proposal format, then validate it:

rdrop organize plan --context library-context.json --proposal proposal.json > organization.json

jq '.plan // error("No accepted changes")' organization.json > reviewed-plan.json

Review accepted changes, needsReview and unmentioned items.

rdrop cleanup apply reviewed-plan.json --dry-run rdrop cleanup apply reviewed-plan.json --yes

Plans keep existing tags and can combine new tags with a collection move. Unknown names and destinations fail validation; new tags need explicit naming rules. Account, digest and snapshots are checked before writing. Concurrent edits or partial failures need inspection and a fresh plan. Organizing and recovery.

Use your agent

The Codex and Claude plugin bundles a shared organizing skill and a read-only MCP connection. Install instructions also cover direct setup for other local clients.

rdrop connect mcp                         # client configuration, without tokens

rdrop mcp serve # read-only tools over stdio rdrop mcp tools --search 'organize tags' # discover relevant schemas offline rdrop mcp tools --name raindrop_context # inspect one exact schema rdrop mcp serve --official # also include Raindrop's hosted AI reads

Default tools read and plan. Enable writes only for an authorized host that enforces review. The official extension imports documented read tools; its plan limits and service availability still apply. Coverage and comparison with the official server.

You can also run a model directly:

# With your model API key in a private environment:

rdrop agent --model your-tool-capable-model --json \ 'Review the first page of untagged bookmarks. Use existing tags and propose a plan.' > agent-result.json

The model receives actual tool results and returns a response plus exact generated plans. Step, call and time limits bound the run. Local Chat Completions servers and hosted Responses APIs are supported. Jev, Laya and Cloudflare Clef provide typed category decisions; uncertainty stays visible. Model setup and exact commands.

Verified and maintained

A real Qwen/Laya loop classified bookmarks, generated a plan and applied it to a disposable test library while preserving existing tags and notes. The local Executor deployment passed connected-account health and live read checks. Repeat the verification, including its limits: this smoke check is not an accuracy benchmark, and Jev/Clef live inference requires provider credentials.

The product focuses on Raindrop. Model providers and proposal formats are agnostic; Obsidian and other note sources remain future options.

For developers

The public name is rdrop for Raindrop.io. Stable technical identifiers are the raindrop-cli repository, @machineyearn/raindrop-cli npm package, rdrop command and raindrop@machineyearn plugin. Storage support currently focuses on Raindrop.io; model and agent connections are provider-neutral.

A native Go CLI, local MCP server and direct model loop share the command implementation. The REST client, model clients and planning code use the standard library; MCP uses the official Go SDK. ACP configuration supplies this server to an existing ACP agent. Executor offers a smaller portable REST adapter. Docker is available as a packaging option.

Command reference · API coverage · Integrations
Contributing · Security · Changelog

make check               # Go checks, build and generated-doc parity

make check-integrations # npm, Executor and Laya contracts make assets # regenerate the terminal graphic

rdrop for Raindrop.io

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

rdrop for Raindrop.io

Get started

1. Install

Or Node 22+, with optional dependencies enabled:

2. Connect Raindrop

3. Ask your agent

Choose your workflow

Organize with a plan

Review accepted changes, needsReview and unmentioned items.

Use your agent

Verified and maintained

For developers