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.

When an alert fires at 3 a.m., the live chart, the runbook, and the fix are already on one page of Oxynote, a self-hosted technical wiki. The chart is a Live Metrics block that runs its own Prometheus or SQL query and draws a time series, bar chart, or gauge. Several such blocks side by side make a dashboard inside the page. Around it, the editor works like Notion, with checklists, callouts, titled code blocks, Mermaid diagrams, Figma embeds, images, and files. Internal APIs get Stripe-style reference pages with the endpoint, a curl example, and a sample response beside the explanation. Mark a page reviewable and every edit lands in a draft. A block-aware diff shows renamed endpoints, fields, and reworded sentences in one red and green view until a reviewer approves. Freshness hooks watch GitHub files, container images, web pages, or dates, and remind maintainers when something a page depends on changes. Teammates edit together live and see who holds which block. Comments attach to a word, a diagram line, or a whole chart, with replies and an inbox for mentions. The Rubber Duck assistant edits pages and runs block queries with Anthropic, OpenAI, Google, OpenRouter, or a local Ollama model, and MCP lets Claude Code and Codex read and write the docs. 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.

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.

Folio is a self-hosted team wiki that stores every page as a plain Markdown file in a Git repository you own, while your team writes together in the browser in real time. People work in Reading, Live edit, or Source mode, keep editing offline until the connection returns, and watch changes land in the page history as commits they can restore. Data tables with nine column types, filters, and views sit beside the documents, and forms write submissions straight into those tables without requiring an account. Whiteboards, Mermaid diagrams, and a visual diagram editor cover the pictures, while uploads like PDF, Word, Excel, and PowerPoint files open as previewable pages inside the tree. Confluence spaces import with their trees, images, and whiteboards converted, so a migration keeps its structure instead of flattening into a pile of attachments. AI agents read and write the same pages through an MCP server with 41 tools, authenticated by personal tokens or OAuth 2.1, and the built-in assistant answers questions read-only or makes supervised edits. Administrators control access down to a single page, sign people in with SAML, SCIM, or OpenID Connect, hand out expiring share links, and publish a space as a public read-only website. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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.

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.

Hatchdoor gives your Markdown notes two front doors at once: a fast web interface for you, and an MCP endpoint where AI agents read and edit the very same vault. Point it at any folder of Markdown files, an existing Obsidian vault included, and it indexes everything into a disposable SQLite read model that rebuilds itself from your files if deleted. In the browser you browse folders, follow wikilinks that survive renames, explore backlinks and graph views, and search by keyword or meaning across every vault you mount. The live editor shows Markdown syntax only on the line you are editing and saves automatically, while concurrency checks refuse a save when the note changed underneath you. Agents connect with their own token and start read-only; turn writes on and Claude Code, Codex, Cursor, or Hermes can create, edit, move, and link notes through the same checked operations the interface uses. Saved queries in Obsidian's Bases syntax render as live tables, attachments preview inline, and optional git integration commits and pushes every change back to your vault's repository. 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.

With 1,200+ GitHub stars since its April 2026 launch, Arkon provides an enterprise-grade knowledge management layer that turns scattered organizational documentation into AI-accessible structured context. The platform runs as a centralized MCP server, compiling your SOPs, policies, technical docs, and institutional knowledge into a versioned wiki with draft-approval workflows, then serving that wiki to Claude Desktop, Claude.ai, Cursor, and any MCP-compatible client through a single permission-scoped endpoint. OAuth 2.1 with PKCE authentication eliminates manual token management — employees authenticate through a browser login while the system discovers endpoints automatically via RFC 8414. The RBAC v2 system supports custom roles with granular permissions, department-scoped AI Skills, workspace isolation, and comprehensive audit logging so every query and access event is traceable. RAG retrieval powered by pgvector embeddings enables AI clients to search across all organizational documents with source attribution, while the AI Skills system lets teams define reusable instruction sets scoped to specific departments or roles. The architecture runs seven Docker containers coordinated by Compose: PostgreSQL with pgvector for embeddings and metadata, Redis for caching, MinIO for document storage, a FastAPI backend, two ARQ async workers for embedding generation and document processing, and a Next.js frontend portal accessible on port 3119. API keys are encrypted at rest with Fernet, and no telemetry leaves the deployment. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. PolyForm Internal Use licensed.

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.

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.

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.

One endpoint for every MCP server you run: MCPHub gathers local and remote Model Context Protocol servers behind stable URLs, so AI clients connect once and see what you allow. Claude Code, Cursor, and Cherry Studio can use four routes: everything at /mcp, a named group at /mcp/{group}, one server at /mcp/{server}, or semantic tool search at /mcp/$smart. Smart routing runs vector search on PostgreSQL with pgvector and an OpenAI-compatible key, so the model gets a shorter tool list. Servers attach over stdio, SSE, or streamable HTTP, OpenAPI services can be wrapped as MCP tools, and changes apply without downtime. In the other direction, MCP tools can be exported as an OpenAPI 3.0.3 spec for OpenWebUI and other OpenAPI clients. Bearer keys, OAuth 2.0 (client and server modes), and GitHub or Google sign-in in database mode control access, with per-user visibility for servers and groups. Encrypted per-user credentials let one shared server use each person's own key. Logs show tool-call activity, request status, and latency, health checks track each connection, and the dashboard controls which tools, prompts, and resources each server exposes. Large text tool results can be compressed, interactive MCP Apps are proxied through MCPHub routes, and a built-in market lets you browse a server catalog. Typical uses include a team-wide gateway, per-project groups, and direct single-server routes for debugging. 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.

With 2,600+ GitHub stars, MetaMCP solves the MCP server sprawl problem by aggregating any number of upstream servers into a single authenticated endpoint that any MCP client connects to once. Group servers into namespaces — development tools in one, data sources in another — then publish each namespace as its own SSE, Streamable HTTP, or OpenAPI endpoint with API-key authentication in headers or query parameters, or full OAuth per the MCP Spec 2025-06-18 standard. The aggregation engine discovers tools, resources, and prompts from all active servers in parallel, prefixes tool names with server identifiers to prevent collisions, and applies configurable middleware including tool filtering to reduce context-window bloat and description overrides to improve LLM comprehension. The web management UI lets you configure MCP servers with stdio, SSE, or Streamable HTTP transports, toggle servers active or inactive per namespace, create and revoke API keys per endpoint, and inspect discovered tools with their schemas. Nested MetaMCP support enables hierarchical architectures where one MetaMCP instance consumes another, creating multi-level tool organization with automatic name resolution. Compatible with Claude Desktop, Claude Code, Cursor, Open WebUI, and any MCP-compatible client through a single connection URL. The Docker container packages the TypeScript backend with PostgreSQL for configuration persistence, exposing the management UI on port 12005 and MCP endpoints on configurable ports. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Cerbos decouples authorization logic from application code entirely, evaluating human-readable YAML policies in under one millisecond through a stateless Policy Decision Point that requires no application state synchronization or cross-network fan-out. Its custom decision engine benchmarks up to 17x faster than OPA-based alternatives. Access control policies use conditions expressed in Google's Common Expression Language, supporting role-based, attribute-based, and policy-based access control patterns including derived roles, scoped policies, and permissions-aware data filtering that pushes authorization predicates directly into database queries. The PDP exposes both gRPC and HTTP APIs with SDKs for JavaScript, Python, Go, Java, .NET, Rust, PHP, and Ruby, making integration a single function call regardless of tech stack. GitOps-native workflows treat policies as code with Git versioning, CI validation through GitHub Actions, coverage reports, breaking-change detection, and audit logs of every authorization decision for ISO27001, SOC2, and HIPAA compliance. Deployment flexibility spans Kubernetes sidecars, standalone services, systemd daemons, AWS Lambda functions, and WebAssembly-embedded PDPs that run authorization logic directly in browsers, serverless architectures, and edge devices. The Admin API manages policy lifecycle operations programmatically, while the built-in Playground and REPL provide interactive testing environments for policy authoring and debugging. 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.