With over 82,000 GitHub stars and 700,000+ downloads, LobeHub has evolved from its origins as LobeChat into a comprehensive multi-agent AI collaboration platform where humans and autonomous agent teams co-evolve. The platform's Agent Harness architecture functions as an operating system between AI models and applications, handling prompt presets, tool orchestration, lifecycle hooks, planning, filesystem access, and sub-agent management across 25+ model providers including OpenAI, Anthropic Claude, Google Gemini, DeepSeek, Mistral, Groq, AWS Bedrock, Azure OpenAI, and local models through Ollama. Agent Groups enable sophisticated collaboration with sequential, parallel, iterative, and debate orchestration modes, allowing multiple specialized agents to tackle complex workflows simultaneously. The Agent Builder creates production-ready agents from natural language descriptions with auto-configuration, drawing from a marketplace of 505+ pre-built agents and 10,000+ MCP-compatible skills and plugins. Pages provide collaborative document editing with multi-agent co-authoring, while Schedules automate agent runs around the clock without human supervision. The knowledge base leverages PostgreSQL with pgvector for RAG-powered retrieval, and Personal Memory gives agents transparent, editable context that evolves through continual learning. The full self-hosted stack deploys via Docker Compose with PostgreSQL, Redis, RustFS for S3-compatible storage, and SearXNG for private web search, all configurable through environment variables. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. LobeHub Community licensed.

Scira is an AI search engine that breaks complex research questions into sub-tasks, retrieves grounded answers from live sources, and cites every claim with clickable links to the original evidence. Formerly known as MiniPerplx and now backed by nearly 12,000 GitHub stars, the platform implements agentic research planning where language models decompose queries, select appropriate tools, retrieve information in parallel, and synthesize responses with inline citations. Seventeen distinct search modes cover Web, Academic, Extreme, X (Twitter), Reddit, GitHub, Stocks, Crypto, YouTube, and Prediction markets, each activating a curated subset of the 28 built-in tools. The Extreme mode deploys a deep research agent with multi-step planning, parallel source retrieval, code execution in sandboxed Daytona environments, and R2 artifact storage for generated charts. Model routing spans 50+ AI providers through a unified configuration layer supporting OpenAI, Anthropic, Google, xAI Grok, and custom models, with per-mode model assignment based on task requirements. The web search tool supports Exa, Tavily, and Firecrawl as interchangeable providers via a Strategy pattern. Lookouts schedule recurring research agents on cron schedules that monitor topics, track changes, and email summaries using Upstash QStash for reliable execution. PostgreSQL stores chat history, user preferences, and custom instructions while Redis handles caching and rate limiting. 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.

Perplexity's answer-engine experience, self-hostable and open-source: Morphic searches the web and writes cited answers. Instead of returning a list of links, it searches the web, reads the sources, and generates a complete answer with inline numbered citations. The generative UI streams rich components, source cards with thumbnails, image grids, syntax-highlighted code, and LaTeX math, rather than plain markdown. Quick mode answers fast; Adaptive mode runs deeper multi-step research. Search backends are pluggable: the Docker Compose bundle ships with a private SearXNG instance so no search API key is required, and Tavily, Brave, and Exa are supported alternatives. LLM providers include OpenAI, Anthropic, Google, Ollama, and any OpenAI-compatible endpoint, with per-mode model mapping - fast, cheap models for quick searches, stronger models for adaptive research, tuning the cost-quality trade-off per query type. An inspector panel exposes tool execution during multi-step research, and AI-suggested follow-up questions keep an investigation moving. Chat history persists in PostgreSQL, results are shareable by URL, file uploads feed context into queries, and optional Supabase authentication adds multi-user or guest access. Because the default search path is your private SearXNG instance, research topics never hit a commercial search API - and with local Ollama models the marginal cost of a query approaches zero. Built with Next.js, TypeScript, and the Vercel AI SDK under Apache 2.0.

Your Gmail, Google Workspace, or Outlook inbox, worked by an AI assistant: Inbox Zero sits on top of the account you already have. Its core idea is rules written in plain English - tell the assistant "label invoices and file the PDF to Drive" or "archive cold outreach unless they mention my company" - and it executes against every incoming message. Emails that need a response arrive with a pre-drafted reply written in your tone, learned from your email history and calendar context. Reply Zero tracks what you owe responses to and what you're waiting on; the Bulk Unsubscriber surfaces newsletters you never read (with read-rate analytics) for one-click unsubscribe-and-archive; the Cold Email Blocker auto-archives unsolicited pitches based on your own definition of "cold." Smart Filing routes attachments - receipts, contracts, PDFs - into the right Google Drive or OneDrive folder, and Slack/Telegram integration lets you read, draft, and triage without opening a mail client. Email analytics show top senders and volume trends. It is not a new email client: everything happens in your real mailbox using native filters. Self-hosting means your mail content and the LLM calls that process it run on infrastructure you control.

ToolHive is an open-source MCP server management platform that lets you run, secure, and orchestrate Model Context Protocol servers in isolated containers, giving AI agents structured access to tools like GitHub, databases, and cloud services without exposing host credentials or network. Every server launches inside its own sandboxed container with a minimal permission file, network access filtering, and encrypted secrets management, preventing misbehaving connectors from reaching beyond their defined scope. The built-in registry provides a catalog of vetted servers you can install with one command, while custom images and package-manager references let you onboard proprietary connectors without writing Dockerfiles. Platform teams deploy the Kubernetes operator to declare MCP servers as cluster resources using Custom Resource Definitions, with automated lifecycle management and multi-namespace isolation. The Virtual MCP Server gateway aggregates multiple backends behind a single endpoint, centralizing OIDC authentication, tool filtering, and composite cross-server workflows so clients connect once instead of juggling separate URLs. An MCP Optimizer analyzes tool schemas via semantic search and surfaces only relevant tools per request, cutting token consumption by up to 85%. OpenTelemetry traces and Prometheus metrics deliver full visibility into tool execution, latency, and request audit trails across every managed server. 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.

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.

With over 77,000 GitHub stars accumulated in under five months since its March 2026 launch, Paperclip has become the default control plane for teams running multiple AI agents in production. Rather than juggling dozens of terminal tabs with Claude Code sessions, Codex instances, and Gemini CLI workers, Paperclip organizes all agents into a company structure with org charts, reporting lines, role-based permissions, and per-agent monthly budgets that trigger hard-stops when exceeded. The platform supports any runtime through its adapter system — Process adapters manage local CLI agents like Claude Code, Codex, Cursor, Pi, and OpenCode as child processes, while HTTP adapters trigger remote agents via webhooks to OpenClaw, serverless platforms, or custom endpoints. Heartbeat-based execution wakes agents on configurable schedules, injecting goal context, budget state, and workspace paths directly into the invocation payload. The Work and Task System provides atomic checkout with execution locks, first-class blocker dependencies, and structured work products to eliminate duplicate effort. Governance features include approval workflows, decision tracking, emergency stops, and full audit trails tracing every mutation to an actor. Deployment runs as a single Node.js process with embedded PostgreSQL locally or scales to external Postgres for production, installable in one command via npx paperclipai onboard. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

WeKnora turns scattered corporate documents into a searchable, reasoning-capable knowledge asset that your team can query in plain language and receive cited, sourced answers. Upload PDFs, Word files, web pages, Feishu wikis, Notion databases, Yuque docs, GitLab repositories, or RSS feeds into structured knowledge bases, and three distinct modes make the content actionable: RAG Quick Q&A retrieves relevant chunks and generates answers with source citations; the ReAct Agent autonomously orchestrates multi-step reasoning across knowledge retrieval, MCP tool calls, web search, and sandboxed code execution to produce comprehensive research reports; and Wiki Mode deploys LLM agents to distill raw documents into an interlinked markdown knowledge base with an interactive knowledge graph, revision history, and one-click rollback. Connect 20+ LLM providers including OpenAI, DeepSeek, Qwen, Claude, and local Ollama models without vendor lock-in, and choose from seven vector database backends (Qdrant, Milvus, Weaviate, and more) for embedding storage. Enterprise features include four-tier RBAC with per-resource ownership and per-workspace audit logs, AES-256-GCM credential encryption, scoped API keys, Langfuse observability tracing for every agent loop and tool call, and a runtime task-queue dashboard for worker-pool governance. Cross-session long-term memory preserves conversational context across interactions. The Agent Skills catalog lets teams install and share sandboxed scripts executed in Docker or E2B containers. A Chrome Extension captures web content directly into knowledge bases. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Character-based chat and storywriting with large language models: TavernAI is the open-source frontend that leaves model choice to you. It generates no text itself; it connects to the backend of your choice - OpenAI (including GPT-4), Anthropic Claude, KoboldAI and KoboldCpp, Oobabooga's Text Generation Web UI, NovelAI, Ollama, and the crowdsourced Horde - so cost, model quality, and content policy are decided by your backend, not the interface. Characters are defined by portable card files in PNG or JSON format with personality, scenario, and example dialogue, and tens of thousands of community-made cards from sites like Chub.ai import directly. Conversations support group chats with multiple characters, a story mode for long-form writing, message swiping to branch between alternative responses, and full editing of any message. World Info injects lore into context when keywords trigger, keeping long roleplays consistent. Themes, custom backgrounds, and configurable generation settings round out the interface. It runs on Node.js, and the SillyTavern project began as a fork of it.

SurveyKing combines survey creation and online examination in a single platform — generate complete questionnaires from plain English via built-in LLM integration, administer timed exams with anti-cheating proctoring, and collect structured data through 20+ question types including matrix questions, cascading selectors, file uploads, and electronic signatures. Built on Spring Boot 3 with a React and TypeScript frontend using the UMI framework and Ant Design components, version 1.12 delivers each question type with independent validation rules, data type controls, and formula calculations. The AI engine connects to mainstream LLMs for survey generation from natural language prompts and provides real-time answer explanations during practice sessions. Exam mode features item banks with Word and Excel bulk import, fixed and randomized question selection, composite paper assembly, live proctoring dashboards with anti-cheating controls, automatic and manual grading with per-question scoring, and PDF score report archiving. The visual logic designer and DSL expression engine handle show/hide conditions, required rules, skip branching, quota controls, randomization, and cross-tabulation analysis with SPSS export. Role-based access controls support multi-user collaboration with department and permission management via Spring Security and JWT authentication. Redis handles caching and queuing while MyBatis Plus manages database operations. Deploy via a single Docker command with embedded H2 for trials or Docker Compose with MySQL for production. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Scoring 64.4 on the WebBench benchmark — state-of-the-art among browser automation platforms — Skyvern replaces brittle XPath-based scripts with Vision LLM reasoning that adapts when websites change their layouts. The platform extends Playwright with AI-powered page methods including page.act(), page.extract(), and page.validate() that accept natural language prompts while still supporting traditional CSS selectors as fallback. The drag-and-drop Workflow Studio offers 17+ block types including navigation, extraction, login, loops, conditionals, code blocks, file download, and file upload — enabling non-technical users to build complex multi-step automations without writing code. Self-hosted deployments support bring-your-own-LLM with OpenAI, Anthropic, Gemini, and Ollama, while the multi-engine architecture allows swapping between Skyvern 2.0, OpenAI CUA, Anthropic CUA, or UI-TARS per task with a single parameter. Built-in infrastructure handles persistent browser sessions preserving cookies and localStorage across runs, automatic CAPTCHA solving for reCAPTCHA and hCaptcha, anti-bot bypass for Cloudflare and DataDome, residential proxy rotation across 20+ countries, and a credential vault integrating with Bitwarden and 1Password for secure 2FA management. Real-time session livestreaming via WebRTC enables visual debugging, while step-by-step action logs with screenshots and full LLM diagnostic traces provide production observability. The MCP server integration exposes Skyvern as a tool for Claude, Cursor, Windsurf, and any MCP-compatible AI agent. Connect to 6,000+ apps through Zapier, Make.com, or self-hosted N8N workflows. Deploy via Docker Compose or pip install with a two-command setup. 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.

Amplication turns entity definitions into production-ready backend services, generating NestJS with Prisma and Apollo GraphQL for Node.js or ASP.NET Core for .NET, eliminating months of boilerplate. The plugin-driven Data Service Generator hooks into code generation lifecycle events, enabling teams to inject CI/CD manifests, proprietary authentication schemes, testing configurations, and cloud-specific deployment targets for AWS, Azure, and GCP without forking the core generator. Blueprint templates encode organizational architecture standards, security policies, and coding conventions into reusable foundations that keep every generated service consistent across the engineering organization. Jovu AI translates natural language requests into entities, relationships, fields, modules, DTOs, and custom API actions, automatically aligning each resource with predefined standards. Generated services include full CRUD operations with input validation, Swagger/OpenAPI documentation, authentication middleware, database-agnostic ORM via Prisma, optional React Admin interfaces, and Jest test scaffolding. Code output syncs to Git repositories as pull requests, preserving standard review workflows while letting developers edit every generated line and add custom business logic. Supports PostgreSQL, MySQL, and MongoDB as database targets. Over 16,000 GitHub stars with enterprise adoption. Apache 2.0 licensed.

Kotaemon is a document QA platform that combines advanced RAG techniques with a clean Gradio-based web interface for chatting with your documents. Built by Cinnamon, the Python backend supports any LLM provider including OpenAI, Azure OpenAI, Cohere, Groq, and local models via Ollama and llama-cpp-python, with a model management panel for configuring LLM and embedding providers from the UI. The default hybrid RAG pipeline combines full-text keyword retrieval with vector similarity search and applies re-ranking to ensure optimal result quality, while multi-modal document parsing extracts content from tables and figures alongside text. Advanced citations link every answer to specific source passages with relevance scores, viewable directly in the built-in PDF viewer with highlighted text spans. GraphRAG indexing via NanoGraphRAG, LightRAG, or Microsoft GraphRAG builds knowledge graphs from document collections for relationship-aware retrieval. Agent-based reasoning supports question decomposition for multi-hop queries using ReAct and ReWOO strategies. Multi-user authentication organizes documents into private and public collections with sharing and collaboration features. The platform supports Docker deployment in lite, full, and Ollama-bundled variants, runs on port 7860, and stores application data in a persistent volume. MCP tool integration enables external system connections for extended retrieval capabilities. On RepoCloud, deploy Kotaemon on a dedicated VPS with Docker, root SSH access, and complete control over your document AI infrastructure, all under the Apache 2.0 license.

OpenSEO provides an alternative to the $100+/month SEO suite monopoly by connecting directly to DataForSEO APIs on a pay-as-you-go basis — you bring your own API key and pay only for the queries you actually make. The platform delivers focused workflows for keyword research with volume, difficulty, CPC, intent, and live SERP inspection; rank tracking with historical position monitoring; backlink analysis with referring domain quality scoring; technical site audits that crawl pages and surface issues; competitor insights comparing SERP positions across keyword sets; and AI visibility monitoring that tracks brand mentions, citations, and prompts across AI models. The integrated MCP server exposes all tools to AI coding agents including Claude Code, OpenClaw, Hermes, and Cursor, while Agent Skills provide reusable SKILL.md workflows that guide agents through complex SEO research tasks. Google Search Console integration reads first-party performance data including clicks, impressions, CTR, and position metrics with URL-level index status inspection. The Prompt Explorer compares how different AI models respond to SEO-relevant queries. Self-host via Docker for personal use or deploy to Cloudflare for team access with automatic database backups. The hosted version at openseo.so adds a 28% markup on DataForSEO requests. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

Modern engineering teams and busy households deploy Octop to run private, autonomous AI agents equipped with persistent memory workspaces, scheduled cron jobs, and direct browser automation. Users can orchestrate specialist agents tailored for software development, IT operations, content generation, and system diagnostics through an interactive React dashboard. The platform connects directly to Discord, Feishu, DingTalk, and WeCom, allowing team members to delegate complex tasks without leaving their everyday messaging apps. An integrated remote desktop and browser control engine lets agents navigate websites, capture screenshots, fill forms, and operate graphical software autonomously. Administrators can assign distinct MBTI personality profiles to agents, establish granular role-based permissions, configure scheduled cron workflows, and integrate custom Model Context Protocol servers for external tool access. Long-term memory persists across conversations through dedicated workspace files, ensuring contextual continuity whenever switching between underlying language models or team collaborators. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Work, personal, business, and school calendars at different providers double-book because no one system sees your real availability - Keeper solves that multi-calendar collision problem. Its pull-compare-push sync engine aggregates events from Google Calendar, Outlook/Office 365, iCloud, FastMail, any CalDAV server, or read-only iCal/ICS feeds, and pushes blocking events to one or many destination calendars so time slots align everywhere. The design is deliberately content-agnostic - it syncs timeslots, not titles or descriptions, so a personal appointment shows as busy time on your work calendar without leaking details. Sync logic is clean: events Keeper creates carry a traceable UID suffix, deletions propagate, and orphaned entries are purged automatically. A token-authenticated aggregated iCal feed combines selected calendars into one subscribable URL for Apple Calendar or Thunderbird. An optional MCP server gives AI agents read-only calendar access over OAuth 2.1 - list calendars and query events by date range, with no write capability. Built with Next.js and Bun under AGPL-3.0, the standalone Docker image bundles web, API, cron, worker, Redis, and PostgreSQL in one container, and self-hosting unlocks every Pro feature - unlimited calendars and one-minute sync intervals - for free.

Upload a report, ask a "what if" question in plain language, and MiroFish builds a small simulated society that plays out the answer before you commit to a decision. It reads your seed documents, whether news, policy drafts, financial signals, or a novel, and extracts entities and relationships into a GraphRAG knowledge graph. Entities from the graph become agents with a profession, a biography, and interest tags, and the app estimates simulation rounds from the simulated time span, with a custom mode for shorter runs. Agents post and react on two simulated platforms at once, a feed-style plaza and a topic community, while a live monitor tracks rounds, elapsed simulated time, and actions. A ReportAgent then plans an outline and writes the prediction report section by section with the InsightForge, PanoramaSearch, QuickSearch, and InterviewSubAgent tools. Afterward you can keep questioning the ReportAgent, chat with any individual agent, or send a survey question to a selected group and read their answers. Typical uses include rehearsing public relations responses, testing policy drafts against likely reactions, and exploring alternate endings for a story. The interface switches between English and Chinese, and you bring your own model: any OpenAI SDK compatible LLM endpoint works, Zep Cloud stores agent memory, and the project suggests starting under 40 rounds because runs consume many tokens. 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.