readability-read-aloud-web-pdf-ai-summary
Free · Open source
Users wanting distraction-free reading
hn-ai-summarizer
FreeOpen SourceSelf-Hosted
Hacker News publishes more good content in a day than most people can read in a week — and most readers either drown in it or miss the stories that matter to them. HN AI Summarizer cuts that problem down to a Telegram message each morning.
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Get This Tool
License: MIT Any use incl. commercial
Local-run terms: Run via Docker Compose on own hardware; full source available under MIT; requires user-provided AI API keys.
Screenshots 2
Pricing
- Model
- Free
Summary
The tool runs on a schedule, pulls the top Hacker News stories, summarizes them with an AI model, and delivers a filtered, translated briefing to a Telegram channel or chat. It lives entirely on your own hardware via Docker, so no data leaves your infrastructure. That self-hosted constraint is the whole point — and also the ceiling. There is no hosted version, no web UI for non-technical users, and no notification channel beyond Telegram. If your team communicates in Slack or needs a browser-based dashboard, this does not cover that.
Bottom line: Deploy this if you want a private, Docker-based HN digest pushed to Telegram each morning — skip it if you need delivery channels beyond Telegram or a UI your non-technical teammates can configure.
Find your fit
Before you choose hn-ai-summarizer
More options in Summarizers. Compare pricing, platforms, and features side by side.
Skimlane
Free · Open source
Researchers and analysts needing consistent page structures
Pros
- Scheduled AI summarization of top Hacker News stories, so you read the signal without manually triaging the full front page each day.
- Keyword-based interest filtering — configured per-user — so stories outside your focus areas (say, anything not tagged AI or security) are excluded before the briefing is assembled.
- Translation support for non-English readers, which means you get the summary in your working language rather than having to run stories through a separate translation step.
- Fully self-hosted via Docker with an MIT license, so your reading preferences and API credentials never touch a third-party cloud service — the alternative being tools that log your queries on vendor infrastructure.
- Telegram delivery with scheduling, which means the briefing arrives at a time you set rather than requiring you to open a dashboard and remember to check it.
Cons
- Telegram is the only supported notification channel. Teams or individuals whose async communication runs through Slack, Discord, or email cannot use this without modifying the source code — there is no plugin or webhook abstraction in the current codebase.
- There is no web UI. Configuration lives entirely in environment variables and the docker-compose file, which means every setting change requires SSH access and a container restart. Non-technical users or shared-team deployments stall at the setup stage.
- The tool has no REST API or output format beyond Telegram messages, so any team wanting to pipe summaries into a second system — a Notion database, a team wiki, a Slack bot — is writing custom glue code rather than using a supported integration.
- With three GitHub stars and zero forks at the time of scraping, community support is minimal. When the upstream Hacker News API or a chosen AI provider changes behavior, the maintainer is a single point of failure. Teams with production-critical digest pipelines move to more actively maintained alternatives at the first breaking change.
About
- Platforms
- Docker, self-hosted servers, Raspberry Pi, NAS
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- July 21, 2026
Best For
Who it's for
- Self-hosted homelab users
- Hacker News readers seeking time savings
- Users wanting multilingual support
- Privacy-focused individuals avoiding cloud services
What it does well
- Daily Hacker News consumption in limited time
- Reading HN stories in non-English languages
- Filtering HN to personal interests like AI or security
- Automated morning briefings via Telegram
Integrations
Frequently Asked Questions
- Is hn-ai-summarizer free?
- hn-ai-summarizer offers a free option. Hosting, model usage, or optional services may have separate costs; check the pricing details and official terms.
- Is hn-ai-summarizer open source?
- Yes. hn-ai-summarizer is open source.
- Can I self-host hn-ai-summarizer?
- Yes. hn-ai-summarizer supports self-hosting on your own infrastructure.
- What platforms does hn-ai-summarizer support?
- hn-ai-summarizer is available on: Docker, self-hosted servers, Raspberry Pi, NAS.
Every morning, Hacker News produces a firehose of links, comments, and discourse that rewards the patient and punishes the busy. HN AI Summarizer addresses this by running a scheduled pipeline: it fetches top stories from Hacker News, passes them through a configurable AI model for summarization, applies keyword-based interest filters you define, optionally translates the output into your preferred language, and delivers the result to a Telegram chat. The entire workflow is configured through environment variables and a docker-compose file, with database migrations handled by Alembic.
The differentiating feature is the combination of translation and personal filtering in a self-hosted package. Most RSS-to-summary tools are cloud-dependent. Here, the vendor states the tool is MIT-licensed and designed to run entirely on your own infrastructure — meaning your reading habits, interests, and API keys stay on your own machine. For privacy-focused homelab users, that is the deciding factor.
The tool fits a narrow but well-defined scenario: a technically capable individual who reads Hacker News regularly, wants to spend less time on it, prefers Telegram for async notifications, and runs a homelab or has a VPS available. It breaks outside those boundaries. There is no REST API for integration with other services, no web-based configuration UI, and Telegram is the only supported delivery target. Teams that want Slack delivery, a shared web dashboard, or programmatic access to the summaries will need to fork the project or build an adapter themselves.
Setup requires Docker, a configured .env file based on the provided .env.example, and an AI provider API key. The docs describe a docker-compose workflow with both production and development variants. CI is handled via Woodpecker, and the test suite is present in the repository, so contributors have a path to extending the notification or delivery logic.
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