by dhvcc · Agent Tool · ★ 54
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Typed pythonic RSS/Atom parser: RSS 2.0/0.9x, Atom 1.0, RSS 1.0 (RDF) and podcasts into pydantic v2 models, plus a CLI
| Stars | 54 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| License | GPL-3.0 |
| Quality Score | 55.3921573645333/100 |
| Last Updated | 2026-07-28 |
| Created | 2020-10-03 |
| Platforms | cli, python |
| Est. Tokens | ~13k |
These tools work well together with rss-parser for enhanced workflows:
Looking for a rss-parser alternative? If you're comparing rss-parser with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Product-Led Growth (PLG) analysis toolkit that detects tech stacks, plans growth loops and builds the loop ite
MCP-native security automation workbench (SDK + CLI + MCP) — authorized testing + static AI/MCP attack-surface
Python library for building with LLMs. One interface across 11 providers (OpenAI, Anthropic, Gemini, DeepSeek,
MCP Server for Facebook ADs Library - Get instant answers from FB's ad library
Instagram Direct messages MCP
Async Python client for the Model Context Protocol with interactive CLI and reactive Web UI, connecting AI mod
Explore other popular agent tool tools:
rss-parser is Typed pythonic RSS/Atom parser: RSS 2.0/0.9x, Atom 1.0, RSS 1.0 (RDF) and podcasts into pydantic v2 models, plus a CLI. It is categorized as a Agent Tool with 54 GitHub stars.
rss-parser is primarily written in Python. It covers topics such as agent-skills, atom, atom-parser.
You can find installation instructions and usage details in the rss-parser GitHub repository at github.com/dhvcc/rss-parser. The project has 54 stars and 4 forks, indicating an active community.
rss-parser is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to rss-parser on Agent Skills Hub include skene, AutoRedTeam-Orchestrator, SimplerLLM. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.