With over 14,000 GitHub stars and 41 releases since its May 2026 launch, Prime Agent delivers a fundamentally different approach to AI coding agents by treating the agent's own operating environment as programmable state that improves through use. The Recursive Language Model architecture provides the model exactly one tool — a persistent IPython kernel — where file operations, shell commands, subagent delegation via rlm() function calls, and context management all happen through code rather than rigid tool-calling schemas. Subagents launch as independent sessions with their own model, kernel, and history, communicating results through agent_message.send() without blocking the parent. The Continual Harness stores supplemental prompts, memories, skill descriptions, and reusable subagent specifications as durable state that the /refine command updates through small, evidence-backed edits with full rollback by ID. Daemon-backed sessions keep running when the terminal disconnects, with automatic context compaction summarizing older messages while preserving recent state. The TUI provides an Agent View for monitoring, switching between, and steering multiple live sessions simultaneously. Autonomous mode operates within configurable turn, token, and time budgets with user-defined quality gates. Persistent goals, heartbeats, and scheduled prompts maintain continuity across terminal sessions. Compatible with Anthropic Claude, OpenAI, Google Gemini, local models via Ollama or vLLM, and Prime Inference endpoints. Install via a single curl command on Linux or macOS. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

DeerFlow 2.0 is ByteDance's ground-up rewrite that transforms what began as a Deep Research framework into a batteries-included super agent harness handling tasks lasting minutes to hours autonomously. Built on LangGraph and LangChain, the runtime orchestrates a lead agent that plans, decomposes, and delegates to sub-agents executing in isolated Docker or Kubernetes sandboxes with persistent filesystem access, while an extensible skills system lets developers add capabilities as Python functions or MCP servers with OAuth token flows. The harness ships with long-term memory using persistent event loops with per-agent isolation, scheduled task execution via cron, context engineering with manual compaction, and a web UI at localhost:2026 for interactive sessions. Model support spans OpenAI GPT-4o/GPT-5, Anthropic Claude via OAuth, Google Gemini, DeepSeek, Qwen via vLLM, and OpenRouter-compatible gateways with per-model pricing configuration. IM channel integration connects Telegram, Slack, Feishu/Lark, Discord, WeChat, WeCom, DingTalk, and Buzz without requiring a public IP — all using long-polling or WebSocket transports. Production deployment uses Docker Compose with nginx reverse proxy, PostgreSQL or SQLite persistence, Redis stream bridges for multi-worker scaling, and lease-based run ownership with automatic orphan recovery. The terminal workbench TUI enables headless operation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Agents with tool use, deep research, a document editor, an IMAP/SMTP email client with AI triage, notes, tasks, and a CalDAV-synced calendar - Odysseus bundles all of it into one open-source, self-hosted AI workspace. It runs local models through Ollama, vLLM, or llama.cpp and cloud APIs like OpenAI and OpenRouter, with a hardware-aware Cookbook that scans your machine and recommends quantized models that fit. Persistent memory uses ChromaDB with hybrid vector-plus-keyword retrieval, web search runs through a bundled SearXNG instance, and agents can use MCP servers, files, and shell access with safety controls, plus custom skills and scheduled agent tasks. A blind Compare mode runs side-by-side model duels with identities hidden and accumulates Elo-style ratings from your votes, so model selection is based on your actual workloads rather than leaderboard claims. Deep research mode - adapted from the Tongyi DeepResearch approach - reads sources through SearXNG and produces cited reports, while the email client tags, summarizes, sets reminders, and drafts replies locally rather than through a third-party mail AI. The writing-first document editor adds AI edits, Markdown and HTML support, and version history. The stack is Python 3.11 with FastAPI, SQLite for state, and a vanilla JS frontend, licensed AGPL-3.0 with zero telemetry. Because agents can read email and execute commands, keep authentication enabled and never expose it as a public unauthenticated service.

Positioned as the open-source NotebookLM alternative for AI agents, SurfSense delivers a live web research platform where your agents access structured data from Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google Maps, Google Search, Indeed, and any page on the open web through one REST API or MCP server. Scheduled and event-triggered agents transform findings into briefs, alerts, podcasts, and presentations, while a built-in knowledge base keeps every discovery searchable with Perplexity-style cited answers using hybrid semantic and full-text search powered by PostgreSQL with pgvector. Upload PDFs, Office documents, images, and audio files, or sync Google Drive, OneDrive, and Dropbox — 50+ file formats supported with AI file sorting that auto-organizes documents by source, date, and topic. The MCP server exposes scrapers, knowledge base, and workspaces as native tools for Claude, Cursor, and any MCP-compatible agent. Cross-country proxy rotation handles Reddit, TikTok, and Google Search scraping with geo-aware sticky sessions and captcha-aware anti-bot handling. The platform features collaborative chats, multi-format document export, git-native knowledge base with Open Knowledge Format export, and a desktop quick-ask panel with global shortcut. Docker Compose deployment manages nine services including Caddy proxy, PostgreSQL, Redis, FastAPI backend, Celery workers, zero-cache real-time sync, and Next.js frontend with automatic Watchtower updates. 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 search experience without Perplexity: Vane deploys Perplexica, an open-source AI answer engine built as the self-hosted alternative. Instead of returning a page of links, it reads your question, searches the live web through the SearxNG metasearch engine, and composes a direct answer with cited sources. Retrieval quality comes from embeddings and similarity search: fetched pages are re-ranked against the query so the model answers from the most relevant passages rather than whatever ranked first. Two query modes cover different needs - Normal mode runs a straightforward web search, while Copilot mode generates multiple reformulated queries and actively pulls content from top matches for harder questions. Focus modes specialize retrieval for academic papers, YouTube, Reddit discussions, Wolfram Alpha calculations, or the general web. The answering model is your choice: OpenAI-compatible APIs or fully local LLMs such as Llama 3 and Mixtral through Ollama, which keeps queries entirely on your infrastructure. Because SearxNG pulls live results, answers reflect current information, and no search history is tracked.

Backed by 27,700+ GitHub stars and actively developed with the v0.9.x architectural overhaul introducing an event-driven plugin ecosystem, ArchiveBox delivers the open-source self-hosted web archiving platform that preserves websites, bookmarks, social posts, media, source code, and research material in durable formats before link rot, platform shutdowns, and censorship erase them permanently. Feed it URLs one at a time or schedule automated imports from browser history, RSS feeds, Pocket, Pinboard, Instapaper, Wallabag, Shaarli, JSON, CSV, HTML bookmark exports, and browser extension captures. Each snapshot stores redundant copies as original HTML, rendered single-file HTML via SingleFile, full-page PDF, screenshot PNG, WARC archive, article text via Readability, favicons, HTTP headers, media files via yt-dlp, git repository clones, and structured metadata in SQLite. The Docker Compose deployment bundles Chrome, wget, curl, yt-dlp, SingleFile, and Readability parsers with automatic dependency management and isolation. Interact through the self-hosted web UI with search, tagging, and admin controls, the comprehensive CLI for batch operations, the REST API for programmatic access, or the Python API for custom integrations. The new abx-plugins system enables community extractors with per-plugin configuration, while the append-only-log architecture provides resumable crawls and audit trails. S3, B2, and Google Cloud storage backends sync archives to remote storage via rclone. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Accepted as a NeurIPS 2025 Spotlight paper and rapidly approaching 6,000 GitHub stars, AI-Researcher from the Hong Kong University Data Science Lab delivers the first fully autonomous scientific research system — a multi-agent platform that takes a list of reference papers and returns a complete research contribution with working code, validated experiments, and a formatted academic manuscript. The pipeline orchestrates five distinct phases: a Resource Collector systematically gathers materials from arXiv, IEEE Xplore, ACM Digital Library, Google Scholar, GitHub, and Hugging Face; an Idea Generator performs gap analysis against semantic embeddings to produce 3-5 novel hypotheses with feasibility scores; an Algorithm Designer transforms concepts into functional implementations; a Validation Engine automates testing, performance evaluation, and iterative optimization; and a Manuscript Creator generates polished full-length papers with figures, tables, and citations. The Gradio-based web GUI provides intuitive tabs for environment configuration, example selection, and real-time monitoring of research progress, while the production deployment at novix.science offers immediate browser access without local setup. Scientist-Bench provides a standardized benchmark comprising state-of-the-art papers across diverse AI research domains for evaluating autonomous research capabilities. The system supports multiple LLM providers including OpenAI, Anthropic, Google Gemini, and OpenRouter models with per-task routing for cost optimization. Deploy via Python with pip dependencies or Docker containerization. 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.

Multiple authors can edit the same LaTeX document simultaneously in the browser with live cursor tracking, conflict-free merging, and instant PDF compilation on every save. Overleaf Community Edition brings the collaborative editing experience that millions of researchers and academics rely on, with no compile time limits, storage quotas, or collaborator caps imposed by the hosted tiers. The web editor provides syntax highlighting, auto-completion, and bracket matching alongside an integrated PDF preview panel powered by a bundled TeX Live distribution supporting pdfLaTeX, XeLaTeX, and LuaLaTeX engines. The file tree panel organizes multi-file projects with separate files for chapters, figures, bibliography references, and style definitions. BibTeX and Biber handle bibliography management, and detailed compilation logs offer clickable error navigation to the exact source line causing each issue. Users upload images, PDFs, and data files directly through the browser, and a template gallery provides starting points for journal articles, conference papers, theses, presentations, and CVs. Over 17,800 GitHub stars and a decade of active development anchor the project. The application runs as containerized microservices including the Node.js web application, MongoDB for persistence, and Redis for session management. 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.

Browser Use Web UI lets you describe a web task in plain English and watch as an AI agent autonomously navigates pages, clicks buttons, fills forms, and extracts information without writing any automation code. Backed by over 16,000 GitHub stars, the Gradio-based interface supports 14+ LLM providers through a unified abstraction layer: OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI, DeepSeek, and local Ollama models are all configurable via dropdown menus without touching code or environment files. The BrowserUseAgent handles interactive single-task automation with step-by-step LLM decision-making and vision-based page understanding, while the DeepResearchAgent orchestrates multi-step research workflows using Langgraph state machines that spawn parallel browser instances with asyncio concurrency control. Custom browser support connects your existing Chrome profile to preserve logins, cookies, and sessions across agent runs, eliminating re-authentication overhead. Persistent browser sessions maintain complete interaction history between tasks for debugging and demonstration. The Docker deployment bundles Chrome, Playwright, and a VNC server in a single container, exposing the Gradio interface on port 7788 and a noVNC viewer on port 6080 for real-time observation of agent behavior. MCP integration via MultiServerMCPClient enables external tool access. Screen recording captures agent workflows as video for review and documentation. 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 question goes in; a cited, long-form report comes out - GPT Researcher is an open-source autonomous research agent. A planner agent decomposes the query into sub-questions, execution agents crawl 20+ web sources in parallel with JavaScript-enabled scraping, and a publisher aggregates findings into a 2,000+ word report with inline citations, exportable to PDF, Word, and Markdown. The Deep Research mode extends this recursively: each result yields follow-up questions that are explored to configurable breadth and depth in a tree pattern, while accumulated learnings, citations, and visited URLs are shared across branches. It also researches local documents (PDF, CSV, Word) alongside the web. LLM and search providers are pluggable, including OpenAI, Anthropic, Google, DeepSeek, and Ollama for models, and Tavily, Google, Bing, DuckDuckGo, and SearXNG for retrieval. It ships as a Python package, a FastAPI server with web frontend, a Docker image, and an MCP server for use inside Claude or Cursor. MIT-licensed.

The most feature-complete open-source alternative to Google's NotebookLM — a self-hosted research platform where you upload PDFs, videos, audio files, and web pages into organized notebooks, then chat with your content, generate multi-speaker podcasts, and run semantic search across everything without sending a single byte to Google's servers. The podcast engine supports 1-4 fully customizable speakers with backstories, personalities, and expertise profiles, generating professional audio dialogue through OpenAI, ElevenLabs, Google TTS, or completely local text-to-speech via Kokoro for maximum privacy. Content processing uses token-based chunking with RAG-powered retrieval grounded in your uploaded sources, while both full-text keyword search and semantic vector search via SurrealDB enable conceptual discovery across all notebooks. The 18+ supported AI providers include OpenAI, Anthropic, Google Gemini, Groq, Ollama, LM Studio, and more — configurable per task so you can route cheap models to summarization and powerful models to analysis. Content transformations extract insights, generate summaries, create study guides, and produce structured outputs from any source material. The MCP integration connects Open Notebook to Claude Desktop, VS Code, and other MCP clients for seamless workflow integration. A full REST API on port 5055 enables complete automation of notebook management, source upload, and podcast generation. Deploy via Docker Compose with the application container, SurrealDB v2 on RocksDB, and optional TTS containers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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.

Most design tools stop at prototyping; Quant-UX also measures how real users actually perform with the prototype. The visual editor creates prototypes that behave like real apps - functional input widgets, animations, form validation, data binding across screens, and business logic modeled with REST requests and decision elements. Design systems are first-class, with components, design tokens, and master screens; if you design elsewhere, drop in image files or import from Figma. Testing is a shared link or QR code - no installs on the tester's side. Define user tasks up front, and Quant-UX records every session: click heatmaps show where users found (or missed) actionable elements, user journey graphs expose lost users, drop-off charts reveal where tasks stall, and success rates and task KPIs are extracted automatically into a dashboard. An A/B test operator wires two design variants into one prototype and compares task duration, success rate, and interaction counts. In-prototype surveys collect qualitative feedback alongside the numbers, and an AI assistant generates prototype fragments like styled forms on request. The RepoCloud deployment runs the full stack - frontend, backend, and WebSocket server containers over MongoDB - so all test recordings and research data stay on your infrastructure.

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.

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.

Live web search plus an LLM of your choice: Farfalle is an open-source, self-hosted answer engine in the Perplexity mold. Queries route through one of several search providers - self-hosted SearXNG for a fully independent stack, or Tavily, Serper, and Bing APIs - and the model composes a cited answer from the retrieved results. Model flexibility is the core design: run llama3, mistral, gemma, or phi3 locally through Ollama for zero per-query cost and full privacy, use cloud models like GPT-4o or Groq-hosted Llama 3 for speed, or route to any provider via LiteLLM. An Expert Search mode uses an agent that plans a multi-step search strategy and executes it for harder questions, and chat history keeps prior research sessions available. The stack is a Next.js and shadcn/ui frontend over a FastAPI backend with Redis rate limiting, shipped as a pre-built Docker image. A browser search-engine entry pointing at your instance makes it the default search from the address bar. Paired with SearXNG and Ollama, the whole pipeline runs with no external API at all.