# AnythingLLM vs RSS Filter AnythingLLM records 512,269 monthly visits with +12.9% month-over-month growth and Freemium pricing. RSS Filter records 0 monthly visits with 0% growth and Free pricing. | Metric | [AnythingLLM](https://openaitools.app/tool/anythingllm) | [RSS Filter](https://openaitools.app/tool/rss-filter) | | :--- | :--- | :--- | | Website URL | https://anythingllm.com | https://rssfilter.sgn.space | | Categories | Large Language Models (LLMs), AI Chatbot, AI Agent, AI Assistant | Large Language Models (LLMs), AI Productivity Tools, AI Assistant | | Pricing Model | Freemium | Free | | Monthly Visits | 512,269 | 0 | | MoM Growth Rate | +12.9% | 0% | | Primary Market | United States | Global | | Direct Visits | 200,729 | 0 | | Review Score | 4.7 | 4.5 | | Saved Count | 3 | 0 | | Supported Platforms | Website | Website | ## AnythingLLM AnythingLLM is a private AI assistant designed around a single idea: you shouldn't rent your own intelligence. It runs on your laptop, desktop or a server you control, giving you a chat and agent workspace with document knowledge, web search, background jobs and custom skills — with no account, no mandatory API keys and no token meter running in the background. After downloading a single installer you pick a model, either one bundled locally or one auto-recommended for your hardware, and start working in a few clicks. Its standout capability is a fully on-device Meeting Assistant. It listens to calls locally, transcribes them, and produces summaries, action items and key decisions without a bot joining the meeting and without sending audio to a cloud service. Combined with document knowledge and background jobs, that turns meeting context into searchable material that later chats and agents can draw on. A Magic dictation feature works in the other direction, refining speech into text in real time while staying aware of what's on screen. The project is open source under the MIT license, with a large contributor community and millions of downloads, and it scales from a single desktop install to a self-hosted multi-user deployment on your own servers. AnythingLLM's product line now spans the desktop app, an Android app that runs small models on-device and pairs with your desktop, and a hosted cloud option for teams that prefer not to manage infrastructure. **Pricing & Plans:** The desktop app is free to download and use, with no account required. Open-source and MIT licensed, and free for organizational self-hosting; a hosted cloud option is available for teams. - **Local document knowledge:** Drop files, notes or sites into a workspace and every document becomes part of the agent's knowledge base without leaving your device. - **On-device meeting assistant:** Records, transcribes and summarizes any meeting locally, delivering action items, key decisions and full transcripts when the call ends. - **Bring any model:** Run bundled local models or connect cloud and API providers, and switch between them per workspace or take advantage of dynamic model selection. - **Background jobs and skills:** Schedule recurring work and define custom agent skills so routine tasks run themselves. - **Developer-friendly and open:** MIT-licensed with a desktop app, Android app, cloud offering and self-hosted multi-user deployment via Docker or your own infrastructure. **Strengths:** Free and open source under the MIT license, with no mandatory accounts or API keys; Meeting transcription and summarization run entirely on your machine, with no bot joining calls; Works with local models and virtually any external LLM provider; Scales from a single desktop install to self-hosted multi-user deployments **Limitations:** Local models can be slower or less capable than the largest hosted frontier models; Running strong models on-device needs reasonably capable hardware; Self-hosted multi-user administration is more work than a simple SaaS signup [Profile (Markdown)](https://openaitools.app/tool/anythingllm.md) ## RSS Filter RSS Filter targets a familiar problem: the feeds pile up faster than anyone can read. Rather than another reader, it is a filtering layer that sits between your feeds and your client. The idea is simple - instead of seeing every item, you see a curated subset that matches what you have already shown interest in. The recommendation engine is built on LLM embeddings and machine learning. As you read articles, the system tracks them and learns which topics matter to you, then ranks and filters new items by semantic similarity. Because it works by replacing the original feed URLs, you do not need to switch readers or change your existing habits; you simply point your client at the filtered sources. Getting started takes an OPML upload. Export your subscriptions from whatever reader you use, drop the file onto the site, and it returns a set of filtered feed URLs. The project is open source - the code lives on GitHub under m0wer/rssfilter - and it is free to use, with a public email contact for feedback. It is the kind of lightweight utility that is best judged by whether it quietly makes your feed manageable again. **Pricing & Plans:** Free to use. RSS Filter is a free tool and open-source project; there are no paid tiers advertised on the site. - **One-Click OPML Conversion:** Upload an OPML export from your RSS client and get all your existing feeds converted into filtered versions automatically. - **Learning From Your Reads:** Every read article feeds a machine-learning model, so recommendations adapt to your real interests over time. - **LLM Embedding Recommendations:** LLM embeddings compare semantic similarity between articles rather than relying only on keywords or categories. - **Works With Any RSS Client:** It works by swapping your original feed URLs, so you keep using your preferred RSS reader with no new app to learn. - **Open Source and Free:** The project is open source on GitHub and can be reported or contacted through a public email address. **Strengths:** Completely free and open source; Works by swapping feed URLs, so no new reader is needed; Learns from your actual reading behaviour rather than static rules; OPML upload makes converting an existing feed list quick [Profile (Markdown)](https://openaitools.app/tool/rss-filter.md) ## Frequently Asked Questions ### How do AnythingLLM and RSS Filter compare in monthly traffic? AnythingLLM has 512,269 monthly visits, while RSS Filter has 0. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? AnythingLLM has a month-over-month growth rate of +12.9%; RSS Filter has 0%. ### How does pricing compare? AnythingLLM: Freemium. The desktop app is free to download and use, with no account required. Open-source and MIT licensed, and free for organizational self-hosting; a hosted cloud option is available for teams. RSS Filter: Free. Free to use. RSS Filter is a free tool and open-source project; there are no paid tiers advertised on the site. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) | | 2 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) | | 3 | [The StoryGraph](https://openaitools.app/tool/thestorygraph-com) | 5,691,605 | +4.5% | Freemium | Mood-based book recommendations and reading tracking | [.md](https://openaitools.app/tool/thestorygraph-com.md) | | 4 | [Kagi Search](https://openaitools.app/tool/kagi-search) | 4,647,605 | +3.2% | Free Trial, Paid | A paid, ad-free search engine that answers to its users | [.md](https://openaitools.app/tool/kagi-search.md) | | 5 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant that runs on your own machine and works from chat apps | [.md](https://openaitools.app/tool/clawdbot.md) | | 6 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Self-hosted AI workspace for local and cloud models | [.md](https://openaitools.app/tool/open-webui.md) | | 7 | [LobeHub](https://openaitools.app/tool/lobehub) | 654,548 | -25% | Freemium | Features a highly customizable agent and plugin workspace, but is less focused on traditional local document RAG workflows. | [.md](https://openaitools.app/tool/lobehub.md) | | 8 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Offers advanced developer frameworks for custom RAG pipelines, but lacks AnythingLLM's ready-to-use user-facing chat application interface. | [.md](https://openaitools.app/tool/llamaindex.md) | | 9 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Offers advanced multi-model management and agent tools, but lacks AnythingLLM's out-of-the-box dedicated document workspace focus. | [.md](https://openaitools.app/tool/librechat.md) | | 10 | [Jan](https://openaitools.app/tool/jan) | 291,894 | -9.6% | Free | Delivers a simpler offline desktop experience for local models, but has less robust multi-document RAG workspace features. | [.md](https://openaitools.app/tool/jan.md) | --- Source: https://openaitools.app/compare/anythingllm-vs-rss-filter More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)