by l0ng-ai · Agent Tool · ★ 449
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Papr A fast, native RSS reader — and a CLI your AI agent can actually drive. Papr is two front-ends over one local database: A desktop reader — fast, native, offline-first. No account, no cloud. , an agent-facing CLI — so an autonomous agent (Claude Code, Codex, OpenCode…) can read, search and triage your feeds straight from the shell. Jump to it ↓ Both read the same database through the shared crate, so the app and the CLI can never drift apart. The desktop app Feeds & folders — subscribe, organize, and import/export OPML. Smart views — All, Unread, Starred, and Read Later, with live counts. Tags & rules — color-coded tags and rules that tag new articles automatically. Full-text — fetch and clean the complete article when a feed ships only a summary. AI — summaries, ask-the-article Q&A, and digests. Bring your own API key. Audio — a built-in player that follows you from article to article. FreshRSS sync — keep read state in step with a FreshRSS server. Local-first — everything stays on your machine. No account, no cloud. Localized — English, Japanese, and Simplified Chinese. Install
| Stars | 449 |
| Forks | 40 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 63.1583317368309/100 |
| Open Issues | 5 |
| Last Updated | 2026-06-27 |
| Created | 2026-05-17 |
| Platforms | claude-code, cli, rust |
| Est. Tokens | ~22k |
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papr is A fast, native RSS reader — plus an agent-facing CLI so your AI agent can read, search and triage your feeds from the shell.. It is categorized as a Agent Tool with 449 GitHub stars.
papr is primarily written in Rust. It covers topics such as agent-skills, agentic, ai-agents.
You can find installation instructions and usage details in the papr GitHub repository at github.com/l0ng-ai/papr. The project has 449 stars and 40 forks, indicating an active community.
papr is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to papr on Agent Skills Hub include claude-code-history-viewer, OpenContext, lovcode. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.