Alexandrie provides a structured knowledge base with an extended Markdown editor, granular per-document permissions, and offline editing through its progressive web app. The CodeMirror 6 editor goes well beyond standard Markdown with colored containers, academic callout blocks, KaTeX math expressions, syntax-highlighted code blocks, footnotes, interactive checkboxes, cards, panels, and a custom snippet system with import and export. Full-text search via the Ctrl+K command center returns instant results with content snippets and relevance ranking across all workspaces. Five permission levels covering None, Read, Write, Admin, and Owner apply per document and per user, while OIDC single sign-on integrates with Google, GitHub, Microsoft, Discord, and any OpenID Connect provider. Documents organize into a hierarchical tree of workspaces, categories, and nested entries with tags, bookmarks, pinned notes, and custom icons. Integrated Kanban boards handle task management within each workspace without switching applications. The PWA installs on any device for full offline editing with seamless sync when connectivity returns. Voice-to-text dictation captures notes hands-free, and one-click ZIP backup exports all documents, files, and settings as a portable archive. Over 2,000 GitHub stars and 41 releases back the project. The Docker Compose stack orchestrates the Nuxt 4 frontend, Go Gin backend, MySQL 8 database, and S3-compatible RustFS object storage. Running on a VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

In seven wizard steps, PandaWiki sets up a product docs, manual, FAQ, or blog site whose built-in AI answers visitors using only your own content. Those visitors can chat with an assistant that cites its sources and accepts image questions, or switch to a docs-only search that lists ranked pages with summaries. Publishing stays under control: each document has three switches, visible in navigation, reachable by URL, and answerable by AI, and nothing appears or gets learned until it is published. Authors write in a Markdown and HTML editor, or import from URLs, RSS and Atom feeds, sitemaps, offline .txt, .md, .xlsx, .docx, and .pdf files, Notion, Yuque, SiYuan, Wiki.js, Feishu, Confluence, and DingTalk. Pages export to Word, PDF, or Markdown. The wizard covers models, domain, HTTP or HTTPS ports, import, publishing, answer testing, and page decoration. One knowledge base can also feed a web widget and DingTalk, Feishu, WeCom, and Discord bots. Administrators get a dashboard of visits, questions, visitor regions, hot documents, and referring domains. Chat models come from Baizhi Cloud, DeepSeek, OpenAI, or Ollama, while vector and reranking models are built in. The open-source edition covers one wiki site, 300 documents, and one admin, and its console and documentation are in Chinese. 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.

DocsMint is a self-hosted knowledge workspace where your team writes documentation once and both people and AI agents retrieve it through hybrid search and a built-in MCP server. Documents live in a rich visual editor with Markdown import and export, organized by folders, categories, and tags, with sharing and version history. Search blends exact title matches, multilingual keyword search, typo-tolerant fuzzy matching, and semantic vectors, then widens results through graph relationships between documents, so a query in one language or phrasing still finds the right page. Every edit quietly refreshes the index in the background; nothing needs manual re-embedding. Agents connect through 22 MCP tools covering search, reading, creation, updates, folders, snapshots, and export, over a local stdio bridge or the HTTP endpoint on your own installation. Category-scoped API keys hand each integration only the slice of the library it may read, edit, or write, while a global key serves trusted automation. The same operations are available through the REST API, a typed TypeScript SDK, and a terminal CLI for scripts. The web application installs as a PWA with offline reading, and AI features run on your choice of an OpenRouter key or a fully local Ollama setup. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Turn scattered meeting notes, policies, postmortems, and documents into a readable wiki that your team can question in plain language. Paste text, upload a file, or point KaaS at a web page, and an AI pipeline pulls out the concepts, decisions, and people, then writes them up as Markdown articles sorted into decision, reference, guide, and concept folders. Ask a question in chat and the answer cites the exact articles it came from, so anyone can open the source and check it. Each article shows tags, a source count, and a table of contents, and every page is stored as a plain Markdown file you can read, edit by hand, or commit to version control. Adding one new document only recompiles that document, which keeps model costs predictable as the library grows. A Builds page lists every submission with its status and attempts, and a failed worker's job is picked up again instead of lost. Derive a topic knowledge base to carve a focused collection out of the wiki for one subject, and let coding agents query the same wiki through an MCP ask tool. Team handbooks, customer onboarding, incident history, and pricing rules are the knowledge that ends up scattered across a dozen files, and this is where it comes back together. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Most wikis die of flat page-and-tag sprawl; BookStack's defining decision is enforced structure - an MIT-licensed PHP/Laravel platform (over MySQL) where content lives in a hierarchy of shelves, books, chapters, and pages, the way a physical library works. A shelf maps to a department, a book to "Engineering Runbooks," a chapter to "Database Procedures," a page to the actual document. That opinionation removes the "where does this go?" friction and keeps knowledge bases tidy as they grow. Editing works both ways: a clean WYSIWYG editor for most users, a Markdown editor with live preview for those who prefer it - switchable per page. Full-text search spans all books or scopes to one, with direct links to individual paragraphs, and include tags let you embed one page's content inside another so shared blocks update everywhere at once. Every edit creates a diffable, revertible revision. Page templates standardize recurring formats, tags add cross-cutting categorization, and built-in diagrams.net integration draws architecture diagrams in place. Authentication covers email/password plus OIDC, SAML2, LDAP, and social login; a full role and permission system locks content down per shelf, book, or page. Pages and books export to PDF, HTML, plain text, and Markdown, a REST API automates content, and the whole thing runs happily on the cheapest VPS you can find.

Confluence and Notion both want your team's documentation in their cloud; Docmost, an open-source collaborative wiki platform, keeps it on your server. The centerpiece is a Notion-style block editor with CRDT-based real-time collaboration: multiple people edit the same page simultaneously and changes merge without conflicts or overwrites. Content lives in spaces - per team, project, or department - with nested page trees, role-based permissions, groups, inline comments, page history with restore, and full-text search across everything. The editor covers tables, code blocks, callouts, KaTeX math, and file attachments, and diagramming is built in rather than bolted on: Mermaid, Draw.io, and Excalidraw all render inside pages, alongside embeds for Airtable, Loom, Miro, and more. Migration paths include Notion, Markdown, HTML, and ZIP archive imports (Confluence, PDF, and DOCX importers ship in the Enterprise edition, along with SSO via SAML/OIDC/LDAP and MFA). The stack is TypeScript with PostgreSQL and Redis, deploys via Docker Compose, runs in air-gapped environments with no external dependencies, and is translated into 10+ languages. The AGPL-3.0 community edition carries no per-seat fees; the project has passed 20,000 GitHub stars since its 2024 launch.

Frappe Wiki is an open-source wiki that turns product guides, help centers, and company handbooks into clean, searchable documentation your whole team enjoys writing. Each space is its own wiki with a separate URL, logo, and access rules, public or limited to chosen roles. The rich text editor handles headings, tables, task lists, code blocks, callouts, images with dark-mode variants, Mermaid diagrams, PDFs, and videos, and stores everything as Markdown. Edits collect in a change request that works like a branch: a reviewer reads a side-by-side diff, then approves, asks for changes, or rejects it, and readers can propose changes too. Every merge adds a version to the page history. Published pages show a page tree, a table of contents, search, PDF download, per-page feedback, and light or dark mode. Analytics report page views, new visitors, top pages, and referrers for the whole wiki, one space, or one page. GitHub Sync keeps a space in step with a folder of Markdown files in a repository. Each page gets meta tags and a generated social card, and the site serves a sitemap, a Markdown copy of every page, and an llms.txt index for AI tools. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Team and product documentation on a fast Vue frontend with PostgreSQL storage: Wiki.js is a Node.js wiki engine. Its distinguishing trait is per-page editor choice: authors pick Markdown with live preview, a WYSIWYG visual builder for non-technical writers, or raw HTML, page by page. Native Git synchronization commits every page change to GitHub, GitLab, Bitbucket, Azure DevOps, or any Git remote - bi-directionally, so edits made in the repository flow back into the wiki - giving documentation version-controlled backup for free. Authentication coverage is among the broadest of any self-hosted wiki: local accounts with self-registration, social login via Google, GitHub, Discord, and Slack, and enterprise SSO through LDAP/Active Directory, SAML, CAS, Auth0, Okta, Azure AD, Keycloak, and generic OAuth2/OIDC, with optional MFA. Built-in full-text search runs on PostgreSQL with zero setup, and external engines like Algolia or Solr can substitute. Page history with visual version comparison, granular group-based permissions per path, nested navigation menus, 50+ integration modules, and full localization round it out. AGPLv3-licensed with a 28k-star community.

Sage Wiki turns a pile of unstructured documents into a fully interlinked, searchable wiki by running them through a five-pass LLM compiler pipeline. Inspired by Andrej Karpathy's vision of LLM-compiled knowledge bases, the pipeline processes source files through diff detection, summarization, concept extraction, image captioning, and cross-reference discovery, with parallel LLM calls and checkpoint/resume for vaults scaling to 100,000+ documents. The typed ontology graph stores entities and relations with BFS traversal, configurable relation types, multilingual synonyms, and a promotion/demotion lifecycle backed by grounding verification and consensus scoring. Multi-format ingestion handles Markdown, PDF, Word, Excel, PowerPoint, EPUB, email, CSV, images, and code files without manual tagging. LLM provider support spans Anthropic, OpenAI, Gemini, Ollama, and any OpenAI-compatible API, with per-pass model routing enabling cost optimization by assigning cheaper models to simpler tasks. The built-in MCP server exposes 17 tools over SSE transport for integration with Claude, Cursor, and any MCP-compatible agent, while native Obsidian vault overlay ensures existing note workflows remain undisrupted. Team deployment supports Git-synced shared wikis, centralized server access, and hub federation across multiple projects. Ships as a single Go binary with Docker Compose multi-arch images serving the web UI on port 3333. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

A notes app that is deliberately not a second brain: notesd keeps your grocery lists, journals, and work notes on a server you run, and syncs them to your phone for fully offline use. The web app and the native Android and iPhone apps each keep a complete local copy, so you can write on a subway and watch everything merge when a connection returns; conflicting edits are combined, or preserved as a linked conflicted copy instead of silently overwriting. Notes are stored as Markdown, so exporting your data or mirroring it to a folder of .md files is always one command away. Tags typed anywhere in a note, including nested ones like #home/garden, collect automatically in the sidebar, and Spaces keep work, personal, journal, and recipes in separate contexts. Full-text search runs across titles and bodies, indexed and ranked both on the server and on your phone. Individual notes can be locked with AES-256-GCM encryption performed on your device, unlocked by password, passkey, or biometrics, while the server only ever stores ciphertext. A few accounts per server, each with its own database, make it easy to host notes for family or friends. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

Chat with your own documents: AnythingLLM, from Mintplex Labs, wraps retrieval-augmented generation (RAG) in an open-source application anyone can run. You organize content into workspaces, each an isolated namespace with its own documents, vector embeddings, chat history, and settings, so one instance can hold several separate knowledge bases. Upload PDFs, DOCX, TXT, and other formats, or scrape web pages; the built-in collector parses and chunks them into a vector database (LanceDB by default, with Pinecone, Chroma, Qdrant, and others supported). Answers cite their source documents. It works with both cloud LLMs (OpenAI, Anthropic, Gemini) and local ones via Ollama or LM Studio, and the embedding model is separately configurable. Beyond RAG chat, it includes AI agents that can browse the web and run tools, an embeddable chat widget for your website, a developer API, and multi-user mode with admin, manager, and default roles plus per-workspace access control. Context assembly is smarter than naive RAG: pinned documents, attached files, vector search hits, and recent chat history are combined under a token budget so the model's context window is filled efficiently, and each workspace supports multiple independent conversation threads against the same knowledge base. Because the embedding model, vector store, and chat LLM are all independently swappable, you can move between providers without re-ingesting a single document. The stack is Node.js with a React frontend, MIT-licensed.

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.

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.

Tela keeps a team's documentation as canonical markdown in a self-hosted wiki that AI agents read, search, and write alongside humans through a built-in MCP server. People edit together with live multi-cursor collaboration, threaded comments, backlinks, and full revision history, so every page shows who changed what and why. PostgreSQL full-text search works immediately, and adding an embedder unlocks semantic retrieval and grounded ask-your-docs answers that cite their sources. Connect Claude, Cursor, or another MCP client with a personal access token and the agent can search the wiki, draft and patch pages, answer comment threads, build spreadsheets with real formulas, and assemble presentation decks exportable to PDF and PPTX. Atlas, the built-in documentation engine, points at a git repository or Jira project and drafts cited wiki pages, then keeps them fresh as the sources change. Teams organize work into spaces, invite members by email, and flip any space public to publish a login-free blog with per-author home pages. Content syncs over WebDAV and exports to zip or PDF, and optional AI features run against your own endpoint or a bundled local Ollama profile, so nothing leaves your server unless you wire it up. 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.