Describe the outcome once, in plain language, and a small crew of AI agents divides the work between them and reports back in the same chat. You type the request in the team chat; Boo Zero, the team lead, splits it into jobs on a shared board and hands each card to the teammate best placed to do it. Teammates run on Claude Code, Codex, Hermes, OpenClaw, or Clawboo's built-in runtime, and one team can mix them freely, so the researcher, the writer, and the coder can each work on their strongest tool. You follow every card live on the board and in the chat, watch the team graph to see who is doing what, and add a reviewer agent when a second pair of eyes matters. Finished work returns to Boo Zero, which pulls the pieces together and answers you in the chat. Ready-made teams from the marketplace cover marketing squads, dev teams, and research crews, and you can bring an API key from Anthropic, OpenAI, OpenRouter and more, a free local model through Ollama, or your ChatGPT subscription through the Codex CLI. Spend is tracked per team with budget warnings before costs surprise you. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

SkillHub gives teams a private, npm-style registry for AI agent skills, so a useful skill package is published once, reviewed, versioned, and installed into a compatible agent from the command line. Upload a package from the web console, the CLI, or the REST API, pick PUBLIC, NAMESPACE_ONLY, or PRIVATE visibility, and track releases with semantic versions plus tags such as beta and stable. Team namespaces keep their own members with Owner, Admin, and Member roles and publishing policies, while full-text search filters by namespace, downloads, ratings, and recency and hides whatever a user may not see. Every submission enters a review queue: namespace admins approve or reject team skills, platform admins decide promotions to the global scope, and each governance action lands in the audit log. A built-in Skill Scanner inspects published packages and shows its report on the skill page, with optional behavioral, LLM, VirusTotal, and Cisco AI Defense engines. Members can star and rate skills, follow download counts, receive notifications, and report problem packages. Skill suites bundle several skills into one versioned collection with an entry skill, scoped API tokens serve the CLI and scripts, and the interface speaks English, Simplified Chinese, Russian, and Korean. Packages live on local disk or S3-compatible storage such as MinIO. 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.

RustXNG gives your AI agents a private web search API that needs no keys, no accounts, and no per-search fees: ask once and get ranked results plus the text of the top pages, ready to ground an answer in real sources. A single request fans out to 180 search engines in parallel, drawn from 226 engine types covering general web, images, video, academic literature, package registries, and news, then merges what comes back with its own ranking that rewards term coverage and canonical-site authority instead of trusting any one engine's order. Engines that time out or keep answering nothing are suspended with backoff and rested automatically, so one dead source never stalls a task, and a repeated query returns from cache in about a hundredth of a second. Call it over HTTP with the familiar SearXNG-shaped JSON, CSV, RSS, or HTML formats, narrow results by domain, engine, or time range, or run the built-in MCP server and hand your agent native search and read_page tools with bounded, truncation-aware responses. Page fetches are hardened against untrusted URLs, an experimental local index can crawl your own corpus and merge it into results, and health, metrics, and per-engine status stay visible through the ops endpoints and the browser UI. 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.

SourceWeft is an AI workstation you host yourself, where agents, your documents, and your model keys work in one place instead of scattering across chat tabs you do not control. Describe a job and a lead agent breaks it down, handing research, exploration, and execution to focused sub-agents that share the same working context and files. Agents draw on a skill library covering presentations, HTML pages, images, meeting summaries, and study guides, and you can add your own skills so good workflows become repeatable. MCP servers, web search, and web extraction connect agents to outside tools, while approved commands run inside a sandboxed environment that cannot touch the rest of your server. Feed it PDFs, web pages, notes, YouTube videos, Notion, Drive, Gmail, or Slack, then follow citations from any answer back to the source material it came from. Bring your own keys for the chat and indexing models you prefer, organize the team into workspaces with roles and access controls, and pick up any conversation from the web app or desktop clients. 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.

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.

A budget model, the launch document that explains it, and the slides that present it can live side by side in one self-hosted office workspace that people and AI agents edit together. Personal and Team Spaces organize Sheets, Docs, Slides, relational Bases, and Boards, with Recent, Trash, file import, and export views keeping everyday housekeeping close at hand. Sharing follows role and node aware access control, including anonymous viewing, so a single table or document can be opened to a reader without exposing the whole space. Data and references stay connected across artifacts as the workspace changes, which keeps a figure corrected in a sheet consistent with the document that quotes it. The Workspace Agent drafts and revises content in isolated Worktrees, verifies its own changes, and hands the result to a person for review before anything reaches the trunk. Several review rounds can happen while humans keep editing in the Browser, and nothing merges until someone approves it. The Workspace CLI connects existing agents to your deployment, so automation can create content, inspect data, render screenshots and PDFs, and run layout checks before review. Sign-in accepts passwords, GitHub, Discord, or application OAuth, and files move in and out as XLSX, DOCX, PPTX, and CSV without a separate conversion project. 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.

Developed by Tsinghua University researchers and validated across more than 700 students, OpenMAIC converts raw prompts, PDFs, Office documents, audio, and video into complete, multi-agent virtual learning environments. The platform leverages Next.js, LangGraph state machines, and a pluggable `@openmaic/storage` layer to orchestrate autonomous AI professors and student avatars that lecture, debate at roundtables, answer inquiries, and illustrate complex equations on a real-time SVG whiteboard. Its Pro Agent Workbench features durable PostgreSQL-backed sessions, twenty specialized curriculum-building skills, and granular JSON Patch slide editing with full `.pptx` import fidelity. OpenMAIC supports rich scene modalities including automated quiz grading, Project-Based Learning milestones, and Deep Interactive Mode offering in-browser code execution, interactive mind maps, and Three.js 3D physics simulations. Built-in audio pipelines connect with VoxCPM2 for zero-shot voice cloning, Azure STT, and FunASR for speech recognition, alongside a dedicated Chromium-FFmpeg rendering microservice for one-click MP4 video exports. Flexible model routing interfaces seamlessly with OpenAI, Anthropic Claude, Google Gemini, Amazon Bedrock, DeepSeek, and local Ollama or Lemonade instances, while OpenClaw integration enables direct classroom generation from Slack, Discord, Feishu, and Telegram. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Customermates delivers a modern CRM purpose-built for teams who want practical customer management without enterprise-heavy complexity. The platform manages contacts, organizations, deals, services, and tasks through clean pipeline workflows while integrating AI agent capabilities, REST API access, webhook events, n8n automation connections, and Model Context Protocol tooling for AI-native operations. Team collaboration features include role-based permissions, comprehensive audit logging tracking every data change, and workspace organization for multi-team deployments. The deal pipeline provides customizable stages with drag-and-drop management, while task assignments and service tracking connect directly to contact and organization records for complete relationship context. API-first architecture exposes all CRM data through documented endpoints enabling custom integrations, reporting dashboards, and third-party tool connections. The n8n integration enables no-code workflow automation for lead routing, follow-up sequences, notification triggers, and cross-system data synchronization. Self-hosting requires only two files — a Docker Compose configuration and environment variables — with the published image at ghcr.io/customermates/customermates:latest running database migrations automatically on first boot. PostgreSQL provides the data layer with no additional infrastructure dependencies beyond a reverse proxy for TLS termination. The Community Edition includes unlimited users, unlimited records, full API access, n8n automation, and audit logging at zero cost. 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.

DB-GPT lets a team talk to its data: ask a business question in plain English, and an AI agent plans the work, writes the SQL, runs it, and hands back charts and a written report. Connect MySQL, PostgreSQL, SQL Server, ClickHouse, DuckDB, Doris, StarRocks, or MaxCompute, or drop in CSV and Excel files, including several at once. Every step appears in a live task view with its query, result table, code, and console output, and the agent pauses to ask clarifying questions, with answer options, when the data cannot settle the matter. Reusable skills package proven procedures, including CSV analysis, SQL analysis, and financial report analysis, and a skill creator helps write new ones. Code executes in a sandbox, parallel sub-agents split larger jobs, and an agentic knowledge-base search answers questions over uploaded documents. Scheduled tasks run saved conversations on a cron timetable with on/off switches and execution history, while MCP connectors link tools like Notion, Linear, Tavily, and GitHub. Pick OpenAI, DeepSeek, Qwen, SiliconFlow, Ollama, or vLLM for the model, then use the application and AWEL workflow tools to build data apps of your own. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Deploy autonomous conversational AI agents and coordinate complex multi-agent workflows through EDDI, an open-source orchestration middleware that turns declarative configuration files into secure, production-grade enterprise assistants. Engineering teams connect AI models from twelve different commercial and local providers, using bilateral Model Context Protocol tools to let external desktop clients and coding assistants interact directly with running conversational services. Autonomous agents collaborate through structured group interaction patterns including round table discussions, peer reviews, Delphi consensus rounds, and devil's advocate debates to refine generated solutions before delivery. Declarative workflow extensions automate external REST API calls with dynamic request templating, extracting structured properties into persistent conversation memory and chaining multi-step service interactions without custom script glue. Built-in secret vaults safely manage sensitive API credentials, while the centralized web dashboard provides live conversation inspection, token quota enforcement, and comprehensive audit logging for regulatory compliance. 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.

Tela keeps a team's documentation as canonical markdown in a self-hosted wiki that AI agents read, search, and write alongside humans through a built-in MCP server. People edit together with live multi-cursor collaboration, threaded comments, backlinks, and full revision history, so every page shows who changed what and why. PostgreSQL full-text search works immediately, and adding an embedder unlocks semantic retrieval and grounded ask-your-docs answers that cite their sources. Connect Claude, Cursor, or another MCP client with a personal access token and the agent can search the wiki, draft and patch pages, answer comment threads, build spreadsheets with real formulas, and assemble presentation decks exportable to PDF and PPTX. Atlas, the built-in documentation engine, points at a git repository or Jira project and drafts cited wiki pages, then keeps them fresh as the sources change. Teams organize work into spaces, invite members by email, and flip any space public to publish a login-free blog with per-author home pages. Content syncs over WebDAV and exports to zip or PDF, and optional AI features run against your own endpoint or a bundled local Ollama profile, so nothing leaves your server unless you wire it up. 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.

Platypus gives a whole team always-on AI agents that reason, call tools, and keep working on your own servers while everyone is offline. Build an agent once by choosing a provider and model, writing its instructions, and capping its tool-calling loop, then reuse that preset across chats and scheduled runs. Agents load reusable Skills on demand and delegate specialist work to sub-agents that appear to the parent as tools. Connect local and remote data through Model Context Protocol servers, or expose an agent to outside agents and chat platforms through A2A endpoints with a token per client. Triggers run agents on a cron schedule, as one-off jobs, or when workspace events such as a card moving on a board occur, and every run records its result. Kanban boards give agents work they can move and update themselves, while notifications and HMAC-signed webhooks push board and workspace events into your own systems with filtering and retries. Facts and preferences are extracted from conversations in the background and injected into future chats, so returning users are remembered. Sandbox backends give agents shell and filesystem access inside an isolated per-workspace environment instead of the host. Organizations and workspaces keep each team's agents and data separate, and blueprints package shared agents, skills, MCP servers, and providers so a new workspace starts pre-equipped. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With 2,000 GitHub stars and 10 releases since its September 2025 launch, HeadlessX delivers a self-hosted browser automation platform that replaces Chromium-based scraping with Camoufox — a Firefox fork performing kernel-level fingerprint spoofing to achieve 0% detection across Cloudflare, DataDome, PerimeterX, and other anti-bot systems where Puppeteer and Playwright regularly fail. The web dashboard provides workspace-based job organization with a visual interface for configuring scrape targets, managing browser profiles, monitoring queue status, and viewing extracted results in real time. The protected REST API accepts requests with API key authentication for programmatic access, supporting HTML extraction, screenshot capture, PDF generation, and structured data parsing with configurable stealth parameters. Profile-based scraping maintains persistent browser contexts with cookie jars, localStorage, and fingerprint configurations that survive between requests — reducing cold-start latency from 25 seconds to under 2 seconds on subsequent requests. Queue-backed workflows enable batch processing of URLs with configurable concurrency, retry logic, and webhook notifications on completion. The Google AI Search integration provides AI-assisted web research workflows through dedicated endpoints. Remote MCP support exposes automation capabilities as tool endpoints for AI agent integration. Deploy via the official CLI with `headlessx init` and `headlessx start` commands, scaffolding a Docker Compose stack with Caddy reverse proxy for automatic HTTPS. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Designed for developers on the go, Yep Anywhere turns any smartphone browser into a full-featured control center for supervising, steering, and reviewing autonomous AI coding agents. Operators can monitor live execution across multiple active projects simultaneously without sitting at a desktop terminal. Real-time reasoning feeds. Instant push alerts for permission prompts. One-tap tool approvals. Developers can unblock pending tasks mid-turn, redirect active workflows, or queue sequential follow-up prompts for automatic delivery at the next safe milestone. An integrated source control viewer displays syntax-highlighted working-tree and commit diffs, allowing reviewers to attach line-level comment bundles directly back into the agent context. Mobile voice transcription lets users dictate instructions straight into running sessions, while photo library integration makes uploading bug screenshots effortless. All agent credentials, CLI configurations, and repository data remain private on the host server without requiring third-party cloud database accounts or proprietary device pairing. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

When an alert fires, OnGrid investigates it for you: an AI operations agent that correlates metrics, logs, traces, and topology, then names the root cause in plain language. A coordinator agent hands each question to specialist SRE, network, or database sub-agents, and the incident investigator walks the service graph for blast radius, queries Prometheus, Loki, and Tempo, and pins the cause to a line of source code before posting its report back to chat. Lightweight edge agents on every host dial out over a single tunnel, so no inbound ports are opened, and operators can reach any machine through an audited browser shell. The agent works through more than 26 read-only inspection tools in a sandbox, while anything that changes production waits behind an approval gate. Ask questions or receive reports in Slack, Telegram, Larksuite, DingTalk, or WeCom, and run it on Anthropic, OpenAI, GLM, DeepSeek, Gemini, Kimi, or any OpenAI-compatible endpoint. A workflow builder turns triggers, agents, tools, and notifications into repeatable automations, and a knowledge vault indexes runbooks, incident history, and repositories for search. Enroll Kubernetes clusters to inspect workloads and manage upgrades, or discover network neighbors, verify them over SNMP, and map them into the topology. Role-based access separates admins, users, and viewers. 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.

Navigating organizational knowledge, visualizing concept graphs, and orchestrating cooperative AI agents converge inside Yuxi, an open-source multi-tenant workspace built for enterprise research and deep archive exploration. Users can upload diverse business documents including scanned PDFs, spreadsheets, and slide presentations to automatically extract structured text blocks, tables, and entity relationships for semantic querying. Knowledge teams can inspect interactive topological graph views to explore connections between company entities, cross-referencing subgraphs against original file sources. Practitioners can configure autonomous agents with specialized subagents, assigning dedicated roles for concurrent research, deep data synthesis, and code execution. Human reviewers can inspect agent thought chains in real time and evaluate interactive confirmation cards before agents execute irreversible external actions or modify shared workspace files. Operators can execute sandboxed tasks that produce downloadable reports, interactive data charts, and rendered HTML pages stored within isolated workspace file systems. Administrators can govern model endpoints, set granular permission boundaries across departments, and monitor token consumption through live system analytics. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

An agent run can finish without errors and still give the wrong answer, so TraceRoot traces every model and tool call, flags the production runs that missed the mark, and helps your coding agent ship verified fixes. Each run becomes a browsable call tree with inputs, outputs, latency, and cost, searchable by session or filter. Instrument with the Python or TypeScript SDK, the agent-native CLI, or any OpenTelemetry exporter, with ready integrations for LangChain, LangGraph, OpenAI Agents SDK, CrewAI, Vercel AI SDK, Mastra, and Pydantic AI. Detectors use LLM judges to score live traffic against the behavior you define and can post alerts to Slack. Judge outputs cluster into signals, then a background coding agent reads the traces and your connected GitHub code in a sandbox and recommends changes down to the commit, file, and line. Datasets, test cases, and scored eval runs compare versions so regressions surface before a release, and dashboards of widgets chart your trace data. The CLI hands your coding agent, such as Claude Code or Codex, the traces, signals, detectors, and evals to work from. Self-hosting keeps all of that trace data on infrastructure you control. 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 (core edition).

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