Neodrop's mobile 1.1.9 release maps the real AI stack: channels, research depth, Skills/MCP, and auto-publish
A LinkedIn-ready English briefing on what Neodrop is, which AI capabilities it exposes publicly, and what shipped in the late-July mobile release.
Neodrop's latest mobile release is not a cosmetic polish pass. Version 1.1.9 on iOS (What's New dated Jul 29) puts Skills, MCP servers, connectors, CLI tokens, push channels, and auto-publish rules into mobile Settings, redesigns Discover as a multi-format gallery, and makes auto-publish a first-class path out of the app.1 Android's late-July listing (updated Jul 28, 2026) pairs the same product direction with a clearer AI assistant and cleaner social cards for Reddit and X.2
For operators who want a standing Neodrop product brief on LinkedIn, that shipping wave is the useful entry point: the product is tightening the loop from research → multi-format production → external distribution.
What Neodrop is
Neodrop is an AI content platform built around channels, not chat sessions. You describe what you want tracked in plain language. The system turns that into a standing assignment: watch sources, produce new pieces on a cadence, and deliver them into your feed.3
Three ideas define the product:
- Channel — an always-on content unit with topic, style, format, and rhythm.
- Source — where the channel looks: public web, RSS, social surfaces, or authorized private connectors.
- Piece — one article, image post, podcast, music track, or video the channel produces, with source citations readers can open.3
That is the product's core distinction from both a general assistant and a classic RSS reader. A chatbot answers when you ask. An RSS reader forwards other people's posts. Neodrop keeps producing new content shaped to the assignment you confirmed.34
Creation is conversational. The AI clarifies forks with short choices, then shows an editable confirmation card covering topic, purpose, format, and cadence. After confirmation, the channel runs on its own. The first real piece is treated as a live validation run, usually a little over ten minutes for simpler setups and longer for complex ones.45
Models and capabilities: the public stack
Public Neodrop materials do not currently publish a fixed foundation-model roster such as a single named GPT, Claude, or Gemini SKU for every task. What they do publish is more operator-relevant: a production stack metered by model calls, research depth, and media synthesis.67
1. Always-on research and production
Each channel run gathers material from configured sources, produces a new piece, and delivers it on the channel's own cadence. Cadence is per channel, not a single global heartbeat.8
Credit cost is dynamic. Pricing FAQ ranges are roughly:
| Format | Typical credit range per piece |
|---|---|
| Article | ~100–360 |
| Visual / image post | ~90–340 |
| Podcast | ~160–240 |
| Video | ~900–1,400 |
Creating a channel also costs roughly one generation (about 220 for an article-style channel, about 1,100 for video). Deeper long reads and HD video sit at the high end.6
2. Five native content forms
Channels can produce and consume five formats: Article, Image Post, Podcast, Music, and Video. Format choice is a standing channel decision, matched to how the reader will use the output — deep read, phone-first scroll, commute audio, song, or social-ready clip.48
3. Source control and connectors
Sources decide what a channel can see. Operators can set must-include and excluded sources in plain language, and optionally require must-include-only collection.9
Separately, Connectors authorize platform accounts the channel may read — Gmail, Outlook, X/Twitter, YouTube, GitHub, Notion, Slack, and many others (help center: over eighty platforms). Public web and public social content need no OAuth; private inboxes and account-gated data do.9
4. Research depth as a plan capability
On paid tiers, pricing explicitly calls out Full Deep Research + Wide Research starting at Pro, plus priority queues and multi-channel parallelism. Studio adds unlimited channels, top-priority concurrency, dedicated growth support, and early access to new models and agents.6
That is the honest public answer to "what models does Neodrop use?":
- production is model-call based and costed by research depth and media synthesis;
- higher plans unlock deeper research modes and earlier access to new models and agents;
- the product surface operators manage is the channel, source set, format, cadence, Skills/MCP, connectors, and publish path — not a one-line model picker in public docs.167
5. Extensibility: Skills, MCP, CLI tokens
The iOS 1.1.9 notes make the extensibility layer explicit on mobile: Settings now covers Skills, MCP servers, connectors, CLI tokens, push channels, and auto-publish rules.1 For an AI-native audience, that is the important architecture signal. Neodrop is positioning itself as an operator environment for recurring AI production work, not only a content reader.
6. Distribution: auto-publish and PublishPort
Auto-publish is built for the last mile. Once a piece is produced, it can leave Neodrop without copy-paste:
- Auto-publish rules send every new piece from selected channels to a connected account.
- Single-piece publish pushes one item to several destinations after human review.
- Standard targets and PublishPort are separate connection paths; PublishPort can batch on a daily schedule as well as publish immediately.10
Limits are equally clear: rules do not judge whether a piece "deserves" to go out, do not rewrite voice for each platform beyond format adaptation, and only post to accounts the user authorized.10 LinkedIn is explicitly in the product narrative for this path.410
What changed recently
Mobile product surface
iOS 1.1.9 (Jul 29 What's New):
- Redesigned Discover as an editorial gallery across video, image, podcast, music, and article cards, with in-feed image swipe and playback.
- Expanded Settings for Skills, MCP servers, connectors, CLI tokens, push channels, and auto-publish rules.
- Auto-publish tooling to connect targets, create and test rules; PublishPort third-party publishing noted for Chinese platforms.
- In-feed AI assistant now shows the channel/article context it is working on.
- Operators can delete their own channel content from the feed.
- Portrait video subtitle placement and several feed/image stability fixes.1
Android (updated Jul 28, 2026):
- Public rebrand line: "We're now Neodrop."
- New AI assistant for starting and refining channels through chat from anywhere in the app.
- Cleaner Reddit and X cards in articles and chat.
- Table rendering and sign-in/stability polish.2
Plans and metering operators should know
Public pricing (USD) currently frames:
- Free: signup credits + limited daily check-ins.
- Starter: about $6.40/mo annualized, 4,000 credits/month, one channel kept daily, standard queue.
- Pro: about $16/mo annualized, 10,000 credits/month + first-cycle launch bonus, multi-channel parallel runs, priority queue, full Deep Research + Wide Research, beta/Discord access.
- Studio: about $160/mo annualized, 100,000 credits/month + larger launch bonus, unlimited channels, top-priority concurrency, dedicated growth support, early access to new models and agents.6
Credits split into permanent and temporary pools; temporary spend first. Exhausted balances hibernate channels until top-up or check-in restores them.7
Why this matters for AI operators
Neodrop is optimizing for a job most AI tools still leave half-finished: turn a standing information assignment into recurring, citable, multi-format output, then route that output to the places your audience already is.
The late-July mobile release is evidence of that thesis moving into day-to-day product ops:
- production controls (Skills/MCP/connectors) are becoming portable;
- distribution (auto-publish rules) is leaving the "export and hope" stage;
- research depth and model/agent access are packaged as plan capabilities rather than hidden one-off prompts.
If you are using Neodrop as a public product-communications surface — for example a weekly English briefing that should also land on LinkedIn — the practical setup is straightforward: keep the channel focused, ground it in official Neodrop sources, and connect LinkedIn under Settings → Auto-publish, then attach an auto-publish rule once the output quality is stable.10
That is the current product map: not a chatbot you babysit, and not a passive feed you wade through — a production system for AI-native content channels.
References
- 1NeoDrop on the App Store
apps.apple.com
- 2NeoDrop on Google Play
play.google.com
- 3What Is Neodrop
neodrop.ai
- 4How to Create a Great Channel
neodrop.ai
- 5Quick start: create your first channel
neodrop.ai
- 6Neodrop Pricing
neodrop.ai
- 7Credits and Usage Explained
neodrop.ai
- 8
- 9How to Choose Good Sources
neodrop.ai
- 10
This story was produced automatically by a channel. One sentence is all it takes for Neodrop to keep producing for you.