MateClaw delivers a multi-agent AI platform where digital employees run as persistent team members with roles, goals, and accumulated skills rather than stateless chat completions. The Spring Boot backend on Spring AI Alibaba provides ReAct iterative reasoning and Plan-and-Execute decomposition on a StateGraph runtime, with parallel delegation between employees and dynamic context pruning for multi-step tasks. Five career templates ship ready (Product Researcher, Customer Support, Knowledge Curator, Data Analyst, Executive Assistant) while custom employees inherit configurable backstories, pixel-art avatars, and dedicated tool bindings. The MCP integration supports stdio, SSE, and Streamable HTTP transports with per-employee tool isolation preventing capability bleed between agents. ACP bridges bring Claude Code, Codex, and other coding agents in as first-class employees. Workflow orchestration composes multiple employees and system actions into publishable linear DSL processes with seven step modes: sequential, fan_out, collect, conditional, await_approval, dispatch_channel, and write_memory. The trigger system wires cron schedules, webhooks, channel messages, employee lifecycle events, content matches, and workflow completions to automated flows. The Admin Runtime Console provides real-time visibility into running employees with token usage tracking and one-click force-recycle. Spring Boot Actuator monitoring, full audit trail, and per-channel error isolation deliver production-grade reliability. 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.

Edict is a multi-agent orchestrator that runs every AI request through a court-style chain: a crown prince agent triages it, a planning department drafts the work, a review department can veto the plan, and specialist ministries execute what survives. Casual chat gets a direct reply, while real commands become kanban tickets whose titles are scrubbed of file paths and metadata. A vetoed plan returns for rework; an approved one is dispatched in parallel to ministries for finance, documentation, engineering, compliance, infrastructure, and HR. Commands arrive through Feishu, Telegram, or Signal channels configured in OpenClaw. The dashboard shows cards by state with heartbeat badges and stop, cancel, and resume controls, plus a department monitor and a memorial archive that turns finished work into five-phase timelines you can copy as Markdown. Nine edict templates add parameter forms and cost estimates, an officials panel ranks agents by merit score while tracking token spend, and per-agent model switching restarts the gateway in about five seconds. Agent thinking, tool calls, and results stream live. A permission matrix limits who may message whom, illegal state jumps are rejected, and every transition lands in an audit log. Worked examples cover competitive analysis, code review, and weekly reports. Dashboard login protects the console, and a systemd unit keeps it running across reboots. 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 drag-and-drop task board that works fine on its own and can also hand cards to AI coding agents, Veritas Kanban shows what each agent is doing, what it changed, and what is waiting for your approval. Start with no agents at all. Cards move through To Do, In Progress, Blocked, and Done, and each one carries subtasks, dependencies, time tracking, comments, and an activity log. When you are ready, connect Codex, Claude Code, Copilot CLI, Hermes, or OpenClaw, give every agent an Intern, Specialist, or Lead permission level, and follow each agent's status and model on a live dashboard. Let a task run in its own Git worktree, read the diff, leave inline comments, approve or request changes, and open a GitHub pull request from the task panel. Squad Chat gives agents one shared channel that posts spawned, completed, and failed events. Workflows chain steps with parallel branches, loops, and human approval gates. Policy rules allow, deny, or hold agent actions for review. Assistants reach the board through an MCP server, a command-line client, or a REST API. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Mayan EDMS stores, classifies, and retrieves millions of documents with automatic OCR, workflow automation, and audit-ready access controls that organizations have relied on for over a decade. Tesseract integration extracts searchable text from scanned PDFs and images in over 100 languages, transforming paper archives into instantly queryable digital collections without manual data entry. The workflow engine routes documents through approval chains using configurable state machines that trigger notifications, enforce retention policies, and maintain complete audit trails for regulatory compliance. Version tracking preserves every revision with full diff capabilities, while GnuPG digital signatures provide cryptographic proof of authenticity and tamper detection for sensitive records. Role-based permissions combined with object-level ACLs and LDAP integration ensure documents remain visible only to authorized users, down to individual file granularity. Full-text search powered by Whoosh or ElasticSearch handles advanced queries across massive document stores with faceted filtering and relevance ranking. The Django REST Framework API enables programmatic upload, metadata extraction, and workflow triggering from external systems. Beyond simple folder hierarchies, metadata schemas, document types, tags, and cabinet structures provide multi-dimensional classification tailored to how your organization actually works. Background processing through Celery handles OCR, conversion, and preview generation asynchronously, keeping the web interface responsive under heavy ingest loads.

A clean alternative to n8n and Zapier that puts AI-native workflows front and center, Fynt is the MIT-licensed workflow automation platform where you drag nodes onto a React Flow canvas, wire them together with typed connections, and let a distributed BullMQ engine execute them — with every step streamed live to your browser over WebSockets so you never wonder what happened inside a run. The node library spans triggers (manual, webhook, cron scheduling), AI providers (OpenAI, Anthropic, and Gemini with structured output parsing), service integrations (GitHub webhooks, Notion databases, Slack channels, Discord bots, arbitrary HTTP endpoints), logic gates (conditional branching, filtering, data transformation), and utility nodes (delay, logging, payload mapping). The execution architecture separates concerns across three services: a Next.js 16 web application serving the React 19 workflow builder and tRPC API, a BullMQ worker processing jobs with node-level retries and checkpointing for crash-safe execution, and a dedicated WebSocket relay server broadcasting real-time run events via Redis Pub/Sub. All stored credentials are encrypted at rest using AES-256-GCM with per-credential initialization vectors. The full-stack deploys as a single Docker Compose stack (web, worker, realtime, PostgreSQL, Redis) or individually via pnpm workspaces in a Turborepo monorepo. Authentication is handled through better-auth with configurable OAuth providers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.