Somewhere between the brilliant novel idea you had in the shower and the finished manuscript sits a hundred hours of outlining, drafting, and continuity wrangling; Show Me The Story compresses that distance. Start with a synopsis and get a full chapter outline you can review, edit inline, or send back for revision before a single paragraph of prose exists. Once the outline is confirmed, the writing page drafts one chapter at a time with streaming output, then waits for your verdict: accept it, or highlight a passage and request a surgical revision that leaves the rest untouched. Characters, organizations, world rules, and relationships live in structured settings, complete with a relationship graph, and are woven into prompts automatically. A dedicated foreshadow system plans setups and payoffs chapters apart, tracks each thread from planted to resolved, and nudges you when one is overdue. After every chapter, extracted facts and a consistency check guard the story against contradictions, and an optional automatic mode keeps the chapters flowing while you supervise. Finished books can be diagnosed and polished in one pass, then exported as a single text file. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Cognee gives AI agents persistent long-term memory that survives across sessions, replacing the traditional stack of separate graph, vector, and session databases with a unified engine running on a single PostgreSQL instance. The memory-native API exposes four verbs (remember, recall, forget, and improve) enabling agents to persist context, retrieve cited answers, prune outdated knowledge, and self-improve from feedback. Under the hood, Cognee combines pgvector embeddings with a PostgreSQL-native graph store and cognitive-science-grounded ontology generation, delivering hybrid retrieval that fuses semantic similarity, structural graph traversal, and lexical search in a single query. Integrations span Claude Code, Cursor, LangGraph, OpenAI Agents, and any MCP-compatible client through a dedicated MCP server on port 8001, while the Python and TypeScript SDKs provide direct programmatic access. The platform supports swappable backends including Neo4j, FalkorDB, Qdrant, ChromaDB, Weaviate, Milvus, and LanceDB for teams with existing infrastructure. Built-in OpenTelemetry tracing, an experimental dashboard with knowledge graph visualization, multi-tenant user isolation, and audit trails ensure production readiness. Deploy via Docker Compose with optional profiles for PostgreSQL, Neo4j, Redis, and the web frontend. Reached v1.0 in April 2026 with 30,000+ stars. 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.

Enterprises requiring production-grade governance for long-running autonomous AI operations can rely on OpenGeni, a self-hosted orchestration platform with human-in-the-loop approvals, Connected Machine execution, and comprehensive audit replays. Operators can configure durable multi-turn workflows that execute continuously toward specified goals without premature termination, automatically pausing when human verification, structured multiple-choice decisions, or critical credential approvals are required. Teams can assign execution workloads across ephemeral cloud sandboxes or route them straight to enrolled Connected Machines to run commands directly against local code repositories without exposing inbound network ports. The integrated web console lets developers inspect live Server-Sent Event activity streams, replay complete turn histories from audit logs, inspect generated artifacts, and cancel or steer in-flight agent tasks on demand. Platform administrators can enforce fine-grained access policies through GitHub App repository bindings, broker temporary role-scoped secrets, and maintain a shared organizational knowledge base where agents propose findings for human review before vector indexing. 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.

Designed as a unified personal AI workstation, QwenPaw operates as an autonomous digital copilot that coordinates scheduled automations, interactive coding sessions, and multi-channel team communication across everyday messaging apps. Users can dispatch long-running research tasks, process office documents including PDF, Excel, and Word files, and execute browser-based data collection without manual intervention. The built-in web console and terminal interface provide full visibility into agent reasoning, allowing operators to inspect intermediate thinking steps, review proposed file edits, and approve sensitive tool calls. Through direct connectors for Discord, Telegram, DingTalk, Lark, and WeChat, teams can trigger specialized skills or query shared workspaces directly from their existing group channels. A self-evolving personal memory system continuously indexes chat interactions and local resources into editable Markdown files, ensuring knowledge persists across restarts and task delegations. Built-in guardrails including a sandboxed execution runtime, tool access policies, and automated skill scanners protect underlying host files from unauthorized modifications during autonomous scripting runs. 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.

CPA Manager Plus is a self-hosted observability dashboard and management panel that tracks every AI request flowing through your CLI Proxy API gateway, breaking down failures, costs, and account health across providers like OpenAI, Anthropic, xAI, and Codex in one interface. When a request fails, drill into the persistent history to see status codes, affected models, latency, and redacted failure evidence without exposing raw response bodies. The cost analytics engine breaks down token consumption and estimated spend by model, provider, account, API key, project, channel, and time range while tracking input, output, reasoning, cache, and service-tier pricing semantics separately. Model prices sync automatically from models.dev with LiteLLM and OpenRouter fallbacks, and you can add local overrides for aliases or internal models. For teams running Codex or xAI accounts, the health inspector reads quota windows, reset evidence, credential state, and workspace status on a configurable schedule, routing credential failures into an action queue for review rather than letting them silently degrade throughput. Deploy the Lightweight Panel to replace your existing CPA management UI without adding another service, or run Full Mode as a single Docker container that adds the Manager Server with persistent SQLite storage for request history, historical analytics, and automated account inspections. Export or import request history as JSONL for external analysis, and back up the SQLite files alongside your encrypted management keys. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Turn company knowledge into structured courses in minutes: ClassroomIO's AI course builder takes your documents, policies, or topic outlines and generates complete lessons with exercises using Gemini, GPT-4o, or Claude — then an in-lesson AI tutor helps employees study the material at their own pace. The SvelteKit 5 and Hono API architecture backs a platform purpose-built for employee compliance training, customer education, and partner certification programs. Programs group courses into cohorts with team management, progress tracking, and goal setting. Live Kahoot-style quizzes drive real-time engagement during training sessions with automatic scoring and leaderboards. Exercises support multiple question types with automatic grading for multiple choice and AI-assisted evaluation for open-ended responses — teachers review and override all AI decisions. Branded certificates with custom IDs reward course completion. Custom domain mapping through Cloudflare lets organizations serve their learning portal under their own brand. MinIO provides S3-compatible storage for documents and video uploads. The REST API and signed webhooks enable programmatic enrollment and completion tracking, while an MCP server on npm supports AI-native authoring workflows. An embeddable widget drops the course catalog onto any website. Better Auth handles sessions and OAuth with optional SSO. 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.

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.

II-Agent is an autonomous AI agent platform that ranked first on the GAIA benchmark by combining multi-step task planning with a full-stack execution environment spanning research, coding, browsing, and content creation. The platform runs a React frontend on port 1420 backed by FastAPI on port 8000, with PostgreSQL for persistence, Redis for task queuing, and MinIO for S3-compatible file storage, all deployable via Docker Compose. Users switch between Anthropic Claude, OpenAI GPT, and Google Gemini mid-conversation using bring-your-own-key authentication. Task domains include deep research with source triangulation, website and mobile app generation from prompts, storybook creation with illustrations, video and image generation via Google Veo and Imagen, presentation building with live collaborative editing, and document manipulation covering PDF extraction, Excel formulas, Word editing, and PowerPoint creation. Built-in connectors integrate Gmail, Slack, GitHub, Notion, Google Calendar, Discord, Dropbox, and Canva for workflow automation. A sandboxed code interpreter runs Python while browser automation with vision capabilities handles web interactions. Custom skills let teams package and reuse workflows. Context management handles up to 120,000 tokens with intelligent window sizing. 3,400+ GitHub stars. Apache-2.0 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.

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 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.

Kodus AI automates pull request code review with inline AI comments across GitHub, GitLab, Bitbucket, and Azure DevOps, supporting any LLM provider at cost with zero token markup. The multi-service TypeScript architecture deploys via Docker Compose, running an API server, background worker, webhooks service, and React dashboard backed by PostgreSQL with pgvector, MongoDB, and RabbitMQ. Integration covers both cloud platforms and their enterprise flavors (GitHub Enterprise Server, GitLab Self-Managed, Bitbucket Data Center) using standard OAuth flows and webhook signing to keep the review loop entirely inside your network. The platform is model-agnostic with Bring Your Own Key support for Claude, GPT, Gemini, Llama, and any OpenAI-compatible endpoint including locally-hosted models. Custom review rules combine your team's coding standards with requirements pulled from Jira, Linear, and Notion, automatically checking every PR against documented specifications. The CLI enables local reviews against working trees, staged diffs, branches, or specific commits, integrating into CI/CD pipelines as pre-merge gates. Source code is never stored and never used for model training, with all data encrypted in transit and at rest. 1,270+ stars and 129+ releases since March 2025. 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.

Memory that survives the session: Hindsight extracts facts, entities, and timestamps from everything an AI agent retains, then lets the agent search or reason over it later. Adding it to an existing LLM client takes a two-line wrapper, and more than 60 integrations cover Claude Code, Cursor, LangGraph, CrewAI, and n8n. Every bank also exposes its own MCP endpoint. Retain sends text, images, or files through an LLM that extracts facts, timestamps, entities, and relationships. Recall runs semantic, keyword, graph, and temporal searches in parallel, merges them with reciprocal rank fusion, reranks with a cross-encoder, and trims to a token budget. Reflect reasons across memories for questions that need synthesis, shaped by per-bank skepticism, literalism, and empathy traits. In the background, related facts consolidate into observations that keep exact quotes and proof counts and are refined, never silently overwritten. Mental models and wiki-style knowledge pages hold standing answers that rewrite themselves as the bank learns. Each user, agent, or project gets an isolated bank with no cross-bank leakage, and Memory Defense redacts or blocks secrets and PII against 45 patterns. The Control Plane adds a Recall Analyzer with traces, a memory constellation graph, and a knowledge page editor. Extraction and reasoning can run on 25+ LLM providers, including local Ollama and llama.cpp. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

AliangBoard puts every Kubernetes cluster you run behind one web panel, where you manage resources yourself or ask an AI agent to do it with your approval. Connect each cluster with a bearer token or basic auth and the panel persists the connection, so switching clusters, namespaces, and workloads takes one click instead of another kubeconfig. More than thirty resource types stay in sync: create workloads, services, ingress, config, storage, and RBAC through structured forms, edit anything as YAML, apply multi-document manifests at once, and delete optimistically with automatic rollback when the API refuses. Pod work goes deep: a tmux-backed exec terminal survives browser refreshes, port-forwards resolve services to their backend pods, files move up and down with progress, and debug containers inject into running pods without restarting them. Day-two operations are buttons, not flag memorization: scale, rolling restart, rollout undo, manual CronJob triggers, and node cordon or drain. Global search, a layered namespace topology, live event streams, and CPU and memory metrics keep orientation effortless. Then there is the operator: an Agent workbench and MCP server let your LLM read logs, debug containers, and propose changes in natural language, while every write waits for a human click and lands in an audit log that names who did what. 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.