Backed by over 45,000 GitHub stars and described as the tool that replaces Notion, Evernote, and Anki in a single Docker container, SiYuan is the privacy-first knowledge management system where every paragraph, heading, and list item is a uniquely addressable content block. The block-level architecture enables bidirectional links, transclusion embeds, and SQL query blocks that dynamically aggregate content across your entire workspace, while the knowledge graph visualization maps relationship networks between documents and blocks. Built-in databases support table views with relation and rollup columns, filter composition, sorting, and template-based calculations for structured data management alongside freeform notes. The FSRS spaced repetition engine turns any content block into a flashcard with scientifically calibrated review scheduling, eliminating the need for separate memorization tools. AI integration connects to OpenAI-compatible APIs for writing assistance, translation, summarization, and Q&A chat, with semantic search using embeddings and reranking for intelligent content retrieval. The Bazaar community marketplace delivers plugins, themes, templates, and widgets through a managed extension system with TypeScript plugin APIs. End-to-end encrypted synchronization works across S3-compatible storage, WebDAV servers, or SiYuan's own cloud service, while Tesseract OCR extracts searchable text from images and the web clipper captures pages from Chrome, Edge, and Firefox. Export targets include Markdown with assets, PDF, Word, and HTML. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Every line an indentable bullet, every bullet a first-class block that can be referenced, embedded, and queried anywhere: Logseq is a privacy-first, local-first knowledge platform built around the block outliner. The daily journal is the system's beating heart - each day opens a fresh date-stamped page where tasks, meeting notes, and fleeting ideas land as blocks without filing decisions, then connect later through [[wikilinks]] with automatic bidirectional backlinks and ((block references)) that transclude any bullet into any page. Everything persists as plain Markdown or Org-mode files on disk - git-friendly, greppable, and owned forever, with sync via iCloud, Dropbox, Syncthing, Git, or an optional end-to-end encrypted service. Built-in tooling goes beyond notes: TODO/DOING task states with scheduling, native PDF annotation with area highlights, spaced-repetition flashcards, whiteboards for visual thinking, Zotero integration for researchers, and Datalog-powered queries that build dynamic views across the entire graph. A marketplace of hundreds of community plugins and themes adds AI chat, Ollama local-model integration, and custom workflows. Written in Clojure/ClojureScript, AGPL-3.0 licensed with 320+ contributors, and completely free - the local-first Roam for people who refuse subscriptions and lock-in.

For people whose notes number in the tens of thousands, Trilium Notes is the hierarchical note-taking application built specifically for large personal knowledge bases - actively maintained as TriliumNext. Notes arrange into arbitrarily deep trees where every note is both content and container, and cloning lets a single note live in multiple places at once - bash notes belong under both Linux and Scripting, and Trilium refuses to make you choose. A WYSIWYG editor handles rich text, tables, math, and syntax-highlighted code blocks with Markdown-style shortcuts, while dedicated note types cover Excalidraw sketches, mind maps, geo maps with GPX tracks, relation maps that visualize connections between notes, and tables with typed columns. The attribute system is the power layer: labels attach queryable metadata (#year=1999, #author), relations create named links between notes, and both inherit down the tree - feeding full-text search, saved queries, and scripting. Scripting is Trilium's deepest differentiator: JavaScript code notes run on events like note changes or hourly schedules, build custom widgets, and add server-side logic, turning the knowledge base into a programmable platform. Protected notes encrypt sensitive content, note hoisting focuses on subtrees, and the self-hosted server syncs desktop clients across devices.

TriliumNext organizes notes in an infinitely deep tree where any single note can be cloned into multiple branches without duplication, building personal knowledge bases that mirror how ideas actually connect rather than forcing a single rigid folder hierarchy. Carrying forward the original Trilium project under active community stewardship with nearly 37,000 GitHub stars, the application is built on TypeScript with a CKEditor 5 WYSIWYG editor supporting rich text, tables, images, KaTeX math expressions, Mermaid diagrams, Excalidraw canvases, mind maps, spreadsheets with XLSX and CSV import/export, and code blocks with full syntax highlighting. A built-in JavaScript scripting engine runs on both frontend and backend, enabling custom widgets, automated workflows, scheduled tasks, and direct interaction with external REST services through a typed Script API. Full-text and fuzzy search with attribute-based queries locates any note instantly across databases tested at over 100,000 notes without performance degradation. The v0.104 release introduced importers for OneNote, Notion, Google Keep, Anytype, and Obsidian alongside 16 dedicated security fixes. Per-note AES encryption, OpenID Connect authentication, and TOTP two-factor protection safeguard sensitive content. The sync server keeps desktop clients, the progressive web app, and mobile devices in lockstep with zero third-party cloud dependency. Web Clipper captures content directly from browsers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

A self-hosted "second brain": Khoj indexes your own files and answers questions from them, parsing Markdown (whole Obsidian vaults included), org-mode, PDF, Word, plain text, Notion pages, GitHub repositories, and images described by a vision model, then embedding everything with sentence-transformers into a vector index for semantic search and RAG with cited sources. Any LLM backend works: local models like Llama, Qwen, or Mistral via Ollama, or cloud models like GPT, Claude, and Gemini. You can build custom agents, each with its own persona, scoped knowledge base, chat model, and tools such as web search and code execution. Scheduled automations run recurring research and deliver newsletters or notifications to your inbox, and research mode performs multi-hop web searches with inline citations. Access it from a browser, the Obsidian plugin, Emacs, desktop, or WhatsApp - all clients connect to the same self-hosted instance, making Khoj one of the few AI assistants Emacs users can point at decades of org files. Semantic search means recall works without exact keywords: "that paper about forecasting with transformers" surfaces the right PDF even when you cannot remember its title. Switching LLM backends never requires re-indexing your documents, and with a local model via Ollama, even inference stays on hardware you control - journals, research, and private notes are never sent anywhere. Python/FastAPI stack, AGPL-licensed, with PostgreSQL storage.

The most feature-complete open-source alternative to Google's NotebookLM — a self-hosted research platform where you upload PDFs, videos, audio files, and web pages into organized notebooks, then chat with your content, generate multi-speaker podcasts, and run semantic search across everything without sending a single byte to Google's servers. The podcast engine supports 1-4 fully customizable speakers with backstories, personalities, and expertise profiles, generating professional audio dialogue through OpenAI, ElevenLabs, Google TTS, or completely local text-to-speech via Kokoro for maximum privacy. Content processing uses token-based chunking with RAG-powered retrieval grounded in your uploaded sources, while both full-text keyword search and semantic vector search via SurrealDB enable conceptual discovery across all notebooks. The 18+ supported AI providers include OpenAI, Anthropic, Google Gemini, Groq, Ollama, LM Studio, and more — configurable per task so you can route cheap models to summarization and powerful models to analysis. Content transformations extract insights, generate summaries, create study guides, and produce structured outputs from any source material. The MCP integration connects Open Notebook to Claude Desktop, VS Code, and other MCP clients for seamless workflow integration. A full REST API on port 5055 enables complete automation of notebook management, source upload, and podcast generation. Deploy via Docker Compose with the application container, SurrealDB v2 on RocksDB, and optional TTS containers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Insights LM gives you a NotebookLM-style research assistant that runs on your own infrastructure and answers strictly from the documents you feed it. Build a notebook for a project, drop in PDFs, pasted text, website links, and audio files, then ask questions in plain language and get answers grounded in those sources rather than the open internet. Every answer carries citations you can click to jump straight to the passage it came from, so verifying a claim takes seconds instead of a fresh search. Findings worth keeping become notes saved alongside the notebook, building a private knowledge base that grows with your research. When reading is too slow, generate an audio overview and listen to two hosts discuss your material like a podcast episode, perfect for absorbing a long report on a walk. Teams use it to interrogate internal documentation, onboard new hires against company knowledge, and brief themselves before meetings without uploading confidential files to a third-party service. Because the whole stack is yours, you choose which AI models do the reading, including local models for fully private work. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Instead of burying your documents in a vector index you cannot inspect, LLM Wiki v2 files them into a Markdown wiki you can read, browse, and question. Drop text, Markdown, or PDF files anywhere on the page and each one is catalogued automatically, filed into a folder that says what it holds, and linked to the notes it relates to. Ask a question and the answer cites the exact notes it used, with clickable sources you can open, verify, and correct. New documents update the note on their subject instead of piling up as disconnected chunks, so what you teach it stays taught. A small classifier routes filing and questions through the folder tree, keeping the wiki quick and cheap as it grows, and you can browse the tree, follow see-also links, move or delete notes, and watch the tokens spent by both the model and the classifier. Connect OpenRouter, OpenAI, Gemini, a local Ollama, or any compatible endpoint, and expose the same wiki to Claude Code or Codex as long-term memory they can recall from and write to. Because every note is plain Markdown in a folder you own, the whole knowledge base can live in git beside your other files. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

PenX delivers an open-source structured note-taking application that functions as a personal database disguised as an elegant editor — combining the outline workflow of Workflowy and Roam Research with the structured data capabilities of Tana through MetaTags that transform every note into a queryable database record. The local-first architecture stores all data on-device using PGLite, an in-process PostgreSQL-compatible engine, ensuring data ownership regardless of cloud connectivity. End-to-end encryption protects all synchronized data so that even the sync server cannot read your notes, tasks, ideas, or documents. GitHub-based version control provides out-of-the-box backup and history with full commit-level recovery. MetaTags are the core innovation — attaching structured tags to any note converts it into a database entry with typed fields, enabling table views, filters, and queries across your knowledge base without imposing rigid folder hierarchies. The daily notes workflow encourages free-form capture while MetaTags handle organization automatically, letting you record thoughts without deciding physical location upfront. AI-driven features assist with content generation, summarization, and intelligent search across your personal data hub. Real-time sync keeps web, desktop, and mobile in perfect alignment. Cross-platform availability includes web, desktop for Windows, macOS, and Linux, iOS, and Chrome extension. Deploy the web service via Next.js with pnpm using tRPC and Prisma. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Atomic transforms collections of personal Markdown notes into an AI-augmented knowledge graph by breaking documents down into semantically linked conceptual units. Users capture thoughts, research excerpts, and web clippings as modular notes that the system automatically chunks, embeds, and categorizes with hierarchical tags. An interactive force-directed canvas maps out the entire knowledge base, positioning related ideas closer together based on embedding cosine similarity rather than manual folder hierarchies. Built-in vector search queries across text embeddings directly within SQLite, retrieving precise contextual snippets in response to natural language prompts. The automated wiki engine synthesizes disparate notes into comprehensive reference articles equipped with verifiable inline citations back to original source materials. Integrated conversational agents leverage retrieved knowledge context to answer research questions, surface contradictions across past entries, and draft structured daily briefings. External AI tools can read, search, and update stored knowledge through an embedded Model Context Protocol server endpoint. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Plain chunk retrieval hands an LLM disconnected excerpts; LightRAG builds a knowledge graph from your documents so answers can join facts spread across many files. Ask about one named person, product, or clause and local mode pulls its details. Ask for themes across the whole library and global mode follows the links between entities. Hybrid blends the two, naive falls back to plain chunk search, and mix combines all three. Mix is the default. Upload text, Markdown, PDF, Word, PowerPoint, and Excel files; MinerU, Docling, or the native parser can extract images, tables, and formulas. The admin console manages documents, explores the graph visually, and debugs queries, while a query-only workspace page gives everyday colleagues a clean chat screen that works on phones. A REST API covers indexing and queries, and an Ollama-compatible endpoint lets chat front ends such as Open WebUI use the knowledge base as a model. New files merge into the existing graph without a full reindex, and deleting a document rebuilds only the entities and relationships it touched from cached results. Separate model roles let an inexpensive model extract entities while a stronger one writes answers. An API key or accounts protect the server, and named workspaces keep several knowledge bases apart. Pair it with local Ollama models and no document text leaves the server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Turning chaotic group brainstorming sessions into structured visual diagrams, TeamMapper provides a real-time collaborative mind mapping workspace that teams and classrooms can join instantly without creating user accounts. Workshop facilitators, teachers, and product squads start from a central root topic and branch outward into hierarchical radial trees, using keyboard shortcuts and full undo-redo history to capture ideas at the speed of conversation. Every node can be styled with custom branch and background colors, adjustable font weights and sizes, external reference links, uploaded raster images, and visual pictograms from the ARASAAC library to reinforce memory and visual association. Sharing a live session takes a single click: hosts distribute either a view-only link, a full modification invite URL, or a scannable QR code so remote colleagues and students in the same room can edit branches simultaneously. When enabled by the administrator, an integrated AI assistant can automatically generate initial mind map branches and subtopics from a text prompt to jump-start planning sessions. Completed maps export cleanly to JSON, Mermaid diagram syntax, scalable SVG vectors, high-resolution PNG images, or printable PDF documents, and existing JSON maps can be re-imported at any time for follow-up workshops. Built-in privacy controls automatically purge inactive mind maps and orphaned image attachments after a configurable retention window, simplifying GDPR compliance for schools and enterprises. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Half the architecture sketches on the internet trace back to Excalidraw - the MIT-licensed virtual whiteboard whose hand-drawn aesthetic made technical diagramming feel approachable, at roughly 85,000 GitHub stars. The infinite canvas offers rectangles, ellipses, diamonds, arrows with smart binding and labels, free-draw, text, images, and an eraser, with full undo/redo, zoom, dark mode, and keyboard-first ergonomics. Community shape libraries add thousands of pre-built elements - AWS architecture icons, flowchart stencils, UI wireframe kits - and everything exports to PNG, SVG, the clipboard, or the open .excalidraw JSON format that keeps drawings diffable and portable. Live collaboration works on a share-a-link model with live cursors and a laser pointer for presenting, and it is end-to-end encrypted by design: the room key travels in the URL hash, which never reaches the server, so the WebSocket relay only ever sees ciphertext. The architecture is remarkably light - the app is a static bundle served by Nginx, drawings persist locally in the browser, and the stateless excalidraw-room relay handles multiplayer - so a self-hosted deployment gives unlimited boards and collaborators with near-zero resource cost, replacing per-editor whiteboard subscriptions.

Large language models get a polished front end that can run fully offline: Open WebUI is the self-hosted front end of choice. It talks to local model runners, primarily Ollama, and to any OpenAI-compatible API, so LM Studio, vLLM, Groq, Mistral, OpenRouter, and cloud providers all plug into the same chat interface and can be mixed per conversation. RAG is built in: upload files to knowledge bases or reference them in chat with the # command, backed by a choice of nine vector databases (ChromaDB and PGVector officially maintained) and multiple extraction engines including Tika and Docling, with hybrid BM25-plus-vector search and cross-encoder reranking. Web search results from providers like SearXNG, Brave, and Tavily inject directly into conversations. Extensibility comes from Python tools and functions that run inside the chat, a Pipelines plugin framework, and native MCP support. Multi-user features include RBAC, SSO, and group permissions, and the instance itself exposes an OpenAI-compatible API your own apps can call.