When household readers want a single web portal to search, request, and deliver ebooks and audiobooks without juggling separate indexers or download clients, Shelfmark unifies the entire acquisition pipeline in one self-hosted hub. Universal search mode queries Hardcover, Open Library, and Google Books for rich cover art, series order, and edition metadata before aggregating matching releases across every configured source. Direct search mode queries individual providers immediately for rapid title lookups. You can connect Prowlarr torrent and Usenet indexers, direct web download mirrors, IRC book channels, and Soulseek peers through slskd inside one unified interface. Multi-user accounts support granular request policies where family members or friends submit book or release requests for admin approval, complete with per-user language preferences and custom delivery targets. Completed downloads automatically rename and route files into Calibre, Calibre-Web, Grimmory, BookLore, or Audiobookshelf watch folders, or dispatch directly to e-readers over SMTP email. Built-in authentication supports local credentials, reverse proxy headers, OpenID Connect single sign-on, and existing Calibre-Web user databases. Optional WireGuard VPN with a fail-closed kill switch and Tor routing keep external indexer queries private. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Roughly 43% of all websites and over 60% of the CMS market run on WordPress - the GPL-licensed platform that scales from a personal blog to publishing operations and WooCommerce stores. The Gutenberg block editor composes pages from reusable blocks, and full site editing extends block control to headers, footers, and templates; tens of thousands of plugins and themes cover essentially every capability a site might need, from SEO and caching to membership and e-commerce. WordPress 7.0 "Armstrong" marks the platform's biggest structural update since Gutenberg itself: a React-based DataViews admin replaces the legacy list tables with instant filtering, a provider-agnostic AI Client API ships with connectors for OpenAI, Anthropic, and Google, media processing moves into the browser via WebAssembly, and a universal Font Library manages typography across block, hybrid, and classic themes with local hosting for GDPR compliance. New Breadcrumbs, Icons, and lightbox Gallery blocks reduce plugin dependence, and server-side PHP block registration simplifies development. The REST API and WP-CLI make it automatable end to end. Self-hosting is what WordPress was designed for: your content, database, plugin choices, and upgrade schedule stay entirely under your control, free of wordpress.com plan limits.

Configure each indexer once, not five times: Prowlarr is the indexer hub of the *arr stack, removing the most tedious duplication in a media automation setup. Instead of configuring the same torrent trackers and Usenet indexers separately in Sonarr, Radarr, Lidarr, Readarr, and Mylar3, you add each one once in Prowlarr and it syncs them to every connected app automatically, complete with category mappings; with Full Sync enabled, adding or removing an indexer propagates everywhere, and a tracker URL change is a one-place fix. Coverage is the deepest available: 500+ torrent trackers with definitions added constantly, 24 native Usenet indexers, generic Newznab and Torznab support for anything else, and custom Cardigann YML definitions with JSON and XML parsing for obscure sources. Built on the same .NET/React base as its siblings, it also earns a place as a search tool in its own right: unified manual search queries every indexer simultaneously at a category level, and you can push multiple releases straight to your download clients without touching Sonarr or Radarr. Health checks and status notifications flag failing indexers, per-indexer statistics track success rates and response times so you can cull unreliable sources, and per-indexer proxy support (SOCKS4/5, HTTP, FlareSolverr) handles trackers behind Cloudflare.

Blast off into productivity space with Rocket.Chat SIX, the ultimate team collaboration cosmos! Imagine a place where your messages, tasks, and projects all live in harmony, orbiting around your team's efficiency like a well-organized galaxy. This isn't just any old chat platform; it's a customizable universe where you're the master of your data domain, with the power to tweak, integrate, and innovate to your heart's content. Ready to provide stellar customer service? Engage with your clients in a way that's so contextually on-point, they'll feel like you're mind-reading across the cosmos. Plus, with a chat engine that's like a gravitational pull for user engagement, your app or website will become the center of your users' universe. And for the security-conscious space cadets, fear not! Rocket.Chat SIX is locked down tighter than a spaceship hatch, with end-to-end encryption and a buffet of deployment options to satisfy your security appetite. All this, hosted on RepoCloud, where the cost is as lightweight as zero-gravity. So why settle for a terrestrial tool when you can have a celestial experience? Rocket.Chat SIX: because your team deserves to collaborate in a universe that's light-years ahead!

A flight recorder for production code, Parca profiles CPU and memory continuously and keeps the history to query after something breaks. A slow memory leak or a momentary CPU spike is already on record by the time anyone looks. Point it at any service that exposes pprof endpoints, or deploy the eBPF-based Parca Agent to profile every process on a Linux host or Kubernetes node without touching application code. The agent covers C, C++, Rust, Go, and more. In the web UI, pick a profile type such as on-CPU, narrow it with Prometheus-style label selectors, sum or group by any label, and click a point on the time series to open its flame graph. Switch the same query to a table, add extra panels, or try the alpha Flame Chart and Sandwich views. After a deploy, open the Compare page, set two queries side by side by label or time range, and the functions that gained or lost CPU time stand out as a diff. Native binaries are symbolized from uploaded debuginfo or upstream debuginfod servers. Recent releases add support for OpenTelemetry eBPF profiler profiles and GPU profile types. Optional persistence keeps history across restarts, and a Prometheus-style scrape configuration with service discovery decides what gets profiled. 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.

Instead of a separate chatbot for each channel, Synaplan runs one self-hosted AI assistant for your team, website visitors, WhatsApp line, and inbox, and shows what every reply cost. In the web app, connect OpenAI, Anthropic, Gemini, Groq, Mistral, xAI, Hugging Face, or local Ollama. Each kind of work gets its own model, from chat and image to video and audio, and every answer carries a Free, Low, Mid, or High cost badge. A planner splits a big request into a task graph and sends each step to the model that fits. On your website, one script tag adds a chat widget, and a human operator can take over any conversation live. On WhatsApp Business and email, the assistant replies on the channel where the question arrived. Behind every channel sits one knowledge base: upload PDFs, Word and Excel files, or images with OCR, and semantic search feeds them into answers. Saved tasks run on demand or on a schedule, approvals pause any action that writes, and watched pages mail you a diff when a URL changes. Connections reach Microsoft 365, Dropbox, Nextcloud, ownCloud, WebDAV, CalDAV, Jira, and Confluence. An MCP server and an Anthropic-compatible endpoint let Claude, Cursor, and Claude Code use your instance. Users and groups share folders and assistants, and admins see usage and health. 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.

PilotDeck introduces a WorkSpace-first architecture where each project receives its own isolated file system, memory store, and skill set, preventing context bleed between parallel tasks. White-box memory makes generation, extraction, storage, and retrieval fully visible, letting users audit, edit, pin, and rollback individual entries when the agent misremembers, while Dream Mode consolidates memory fragments during idle windows. Smart Routing auto-detects task difficulty and sends complex calls to flagship models like Claude Sonnet or GPT-4o while routing simple requests to lighter models, achieving claimed 70% cost savings through on-device and cloud co-orchestration with TokenSaver tiering and sticky session binding. Always-on background execution keeps agents running after the user closes the browser, with Discovery and Cron-based scheduling for recurring workflows. The platform natively supports the Model Context Protocol for first-class MCP server integration, community skills via ClawHub on npm, lifecycle hooks intercepting PreToolUse and UserPromptSubmit events, and custom memory store providers. Multi-provider fallback automatically switches to backup providers on timeout or rate-limit errors. The WebSocket and HTTP gateway serves web, CLI, desktop, and Feishu IM channels from a single configuration. 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.

When a buyer asks ChatGPT, Claude, or Perplexity which product to choose, Limelit Open shows whether your brand appears in the answer, where it ranks, and which sources the engines trusted. You define the prompts your market actually asks, register your competitors, and the tracker runs every prompt against seven engines on a schedule you control: ChatGPT, Claude, Perplexity, and Gemini through vendor APIs with web search on, plus Google AI Overviews, Google AI Mode, and Bing Copilot through scraper providers, each result labeled by how it was collected. Every stored answer is searched for your brand and each competitor with the rank of the list item they appear in, so visibility, share of voice, average position, and citation share rest on readable evidence rather than a black-box score. Click any number and you land on the full answer text with matches highlighted, the searches the engine ran, the brands it named, and every cited URL classified as yours, a competitor's, social, informational, or other. A prompt by engine grid makes weak spots obvious, and the built-in MCP server lets Claude or another assistant query the same data in plain language. Runs are capped by a daily ceiling you set, prompts and answers live in one SQLite file, and a single export command dumps the whole instance as JSON or CSVs for your own reporting. 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.

SpiderFoot is an open-source OSINT automation platform, replacing hours of manual reconnaissance with automated intelligence gathering across more than 200 data collection modules. The platform accepts ten distinct target types including IP addresses, domains, hostnames, network subnets, ASNs, email addresses, phone numbers, usernames, person names, and Bitcoin addresses, then feeds them through a publisher-subscriber event bus where each module's findings trigger downstream analysis automatically. SpiderFoot queries Shodan, VirusTotal, HaveIBeenPwned, AlienVault OTX, Censys, crt.sh, WHOIS databases, social media platforms, breach databases, and dozens more sources, with most modules requiring no API keys and many offering free tiers for those that do. The YAML-configurable correlation engine applies 37 pre-defined rules to identify relationships between discovered data points, flagging patterns like shared infrastructure, credential exposure, and domain reputation anomalies. Results export in CSV, JSON, and GEXF graph formats for integration with external analysis tools. TOR integration enables dark web searching, and SpiderFoot can invoke external tools including DNSTwist, Whatweb, Nmap, and CMSeeK for deeper technical assessment. The embedded web server delivers an intuitive dashboard for scan management, data visualization, and result exploration alongside a full command-line interface for scripted automation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Lightpanda is a headless browser built for AI agents and automation that loads and runs web pages without ever drawing them, so crawling, scraping, and agent browsing finish far faster and lighter than in Chrome. You drive it with the tooling you already have: Puppeteer, Playwright, and Chromedp connect over the Chrome DevTools Protocol, Selenium works over WebDriver BiDi, and existing Chrome automation scripts keep running against the new endpoint. Scripts can execute JavaScript on real pages, wait for network activity, read and mutate the DOM, submit forms, and pull structured data out of dynamic sites that plain HTTP clients cannot see. An MCP server mode hands the browser to AI applications as a callable tool, so a model can open pages, follow links, and read content in the middle of an agent workflow. The built-in agent accepts plain-language browsing tasks and can export what it did as PandaScript, a replayable JavaScript file that runs later with no model call at runtime. A fetch command loads one or more URLs and prints the result as HTML or Markdown, which turns page extraction into a single shell step inside data pipelines. In the project's published crawl benchmark it processed pages roughly nine times faster than headless Chrome at a fraction of the memory, so one server can hold many more concurrent browsing sessions. 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.

Your AI coding agent has your API keys in its environment and unrestricted network access, which means one prompt injection away from sending those secrets anywhere. Pipelock closes that gap by sitting as a proxy between your agents and every outbound connection, scanning the actual content of HTTP, WebSocket, MCP, and Agent-to-Agent traffic before it leaves your server. An 11-layer scanner pipeline checks every request against 62 credential patterns covering AWS, GCP, Azure, GitHub, OpenAI, Anthropic, SSH keys, and database URLs, then inspects every response for prompt injection using 29 detection patterns with six-pass normalization that catches base64-encoded, leetspeak, and whitespace-obfuscated payloads. The MCP proxy wraps any Model Context Protocol server (stdio, HTTP, or WebSocket) with bidirectional scanning that detects tool description poisoning and mid-session rug-pull changes via SHA-256 fingerprinting. Every scanning decision produces a cryptographically signed action receipt that third parties can verify offline without trusting the agent or the vendor. The Operator Console provides a web dashboard for reviewing evidence scorecards, receipt timelines, agent sessions, enforcement decisions, and fleet posture at a glance. Cross-request taint tracking catches slow-drip exfiltration attempts that spread a secret across multiple calls. Canary tokens plant synthetic secrets that trip alerts the moment an agent tries to exfiltrate them. Pre-built Prometheus metrics and a Grafana dashboard provide real-time visibility into traffic volumes and block rates. Deploy 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 over 45,000 GitHub stars and 100 million Docker pulls, Milvus is the most widely adopted open-source vector database, powering production AI systems at NVIDIA, Salesforce, eBay, Airbnb, and DoorDash. The distributed architecture separates compute and storage with stateless microservices on Kubernetes, horizontally scaling query nodes for read-heavy workloads and data nodes for write-heavy ingestion independently. Milvus 3.0 introduces lake-native retrieval that builds and serves indexes directly over vector data in object storage and open formats including Parquet, Lance, Iceberg, and Vortex without maintaining separate copies. Native hybrid search unifies lexical BM25 full-text retrieval and semantic vector search in a single engine with metadata filtering, eliminating the need for separate search infrastructure. Hardware-accelerated ANN indexing supports IVF, HNSW, DiskANN, and GPU-based indexes with BitQ 1-bit quantization cutting memory usage by 72 percent. SDKs for Python, Go, Node.js, and Java provide programmatic access, while Milvus Lite offers lightweight embedding for local development via pip install. Server-side aggregation, sorting, faceted search, StructArray for nested document structures, and ColBERT multi-vector scoring move ranking and result processing into the engine. The Path Index enables 100x faster JSON filtering with support for 100,000+ collections per cluster for multi-tenant deployments. Self-hosting deploys via Docker Standalone or Kubernetes with Helm charts using S3-compatible, GCS, or Azure Blob storage backends. 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.

OpeniLink Hub turns a personal WeChat account into a programmable bot platform, with a web console, multi-bot management, and a one-click app marketplace that wires WeChat to Lark, Slack, GitHub, Notion, and twenty other services. Bind accounts by scanning a QR code, then watch every bot's status, expiry window, and message flow from one dashboard. Install marketplace apps without writing code: Lark gains 34 AI-callable tools across calendars, docs, tasks, and meetings, while GitHub brings 36 tools for issues, pull requests, and Actions. Every incoming message fans out in parallel over WebSocket for millisecond pushes, Webhook callbacks to your own servers, and an AI channel that answers through any OpenAI-compatible API. Message tracing follows each message from receipt to delivery, showing exactly which hop stalled when something breaks. Passkey sign-in with fingerprint or hardware keys keeps the console protected, with GitHub and LinuxDo OAuth as alternatives. Reminders, expense tracking, currency conversion, RSS digests, and cron-scheduled pushes run as installable apps, and expiry reminders warn you before the 24-hour reply window closes. Build your own integrations with official SDKs for Go, Node.js, Python, PHP, Java, C#, and Lua, or expose local CLI commands as chat-callable tools with the Runner app. 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 pile of paper becomes a searchable digital archive under Paperless-ngx, the community-maintained document management system. The pipeline is what makes it work: drop a file into the consumption folder (or let it poll an email inbox), and a worker hashes it for duplicate detection, routes it by type, runs OCRmyPDF with Tesseract (100+ languages) on anything without a text layer, and produces an archivable PDF/A with invisible selectable text embedded - so Ctrl+F works on your scans. Then the smart part: a scikit-learn classifier (TF-IDF plus multi-label prediction) trained on your own tagged documents automatically assigns tags, correspondents, and document types to new arrivals, alongside rule-based exact, keyword, and regex matching for deterministic cases. Full-text search includes relevance ranking, match highlighting, autocomplete, and "more like this" similarity search. Apache Tika integration extends consumption to Word, Excel, PowerPoint, and LibreOffice formats. The Django/Angular app adds custom fields, saved views on a customizable dashboard, bulk editing, workflow automation triggered on upload or matching, shareable public links with expiration, and a robust permissions system with per-document access control. Metadata lives in PostgreSQL with Redis-queued Celery workers processing documents in parallel. Your tax records, invoices, and contracts stay on your server - searchable in seconds, never in someone else's cloud.

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.

MISP is an open source threat intelligence platform where analysts log indicators and incidents, see how they connect, and share them with trusted organizations. Each case is an event holding attributes and structured objects such as files, network connections, and email messages, with Markdown reports beside the machine-readable data. A correlation engine links events that share values, including fuzzy-hash and CIDR matches, and warning lists flag benign values before they cause false positives. Taxonomies and galaxies tag events with TLP levels, threat actors, malware families, and MITRE ATT&CK techniques. Analysts explore relationships in an event graph and a correlation graph with a timeline, and build drag-and-drop dashboards with maps and ATT&CK heatmaps. Sharing groups control who sees which event, and instances synchronize with partner organizations with distribution settings down to a single attribute. Free-text, URL, bulk, and STIX imports fill the database, and exports reach Suricata, Snort, Zeek, OpenIOC, CSV, STIX 1 and 2, and RPZ zones. A REST API, the PyMISP library, expansion modules, and workflows enrich data and automate publishing. ZeroMQ and Kafka streams announce every change to connected tools. 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.

Portabase takes a zero-trust approach to database backups: lightweight Rust/Tokio agents deploy next to each database, encrypt dumps with AES-GCM before data ever leaves the host, and poll the Next.js control plane outbound every five seconds requiring zero inbound firewall rules. This architecture contains blast radius if the dashboard is compromised while supporting ten engines with stable backup and restore: PostgreSQL 12 through 18, MySQL 5.7 through 9, MariaDB 10 and 11, MongoDB 4 through 8, SQLite 3.x, Redis 2.8+, Valkey 7.2+, Firebird 3.0 through 5.0, Microsoft SQL Server 2017 through 2022 including Azure SQL, and Docker volumes on Engine 20.10+. Encrypted backups store on configurable backends including local filesystems, any S3-compatible provider (AWS, MinIO, RustFS), Google Cloud Storage, and Azure Blob Storage. Cron-based scheduling with Grandfather-Father-Son retention policies automates backup lifecycle management, while on-demand restore targets any compatible server for cross-environment recovery. The CLI installs agents with a single command and auto-updates when new versions ship. A RESTful API with MCP server integration enables automation from CI/CD pipelines and AI agent workflows. Developed by a non-profit under Apache-2.0. 1,270+ stars and 174 releases since October 2024. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console.

Doccano is a text annotation platforms for building machine learning training datasets. The web-based interface supports text classification for sentiment analysis and document categorization, sequence labeling for named entity recognition with overlapping entity support and relation extraction between labeled spans, and sequence-to-sequence annotation for text summarization and machine translation pairs. Collaborative annotation enables multiple annotators to work on the same project simultaneously with per-user progress tracking, annotation guidelines, example assignment to specific members, and filtering by assignee. Auto-labeling integrates with external machine learning model APIs through configurable request and response mapping templates, allowing pre-annotation that annotators can review and correct. Data import accepts plain text, JSONL, CoNLL, and Excel formats, while export produces JSONL and CoNLL datasets compatible with spaCy, Hugging Face Transformers, PaddleNLP, and other training frameworks through the doccano-transformer library. The Django backend with Django REST Framework exposes a complete RESTful API for programmatic project creation, dataset management, and annotation retrieval via the official doccano-client Python library. Celery handles background tasks including dataset import and export processing with Flower providing task monitoring. One-click deployment supports AWS CloudFormation and Heroku alongside Docker Compose for self-hosted environments. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.