Run a whole fleet of AI agents as managed services, each with its own model, memory, schedules, and sandboxed workspace, from one admin console. Create an agent, point it at OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint, store its API keys encrypted, and it is ready to chat in the browser. People sign in with a device key and get a session list, streaming replies, and file attachments. The Agents table shows status, last activity, sessions, errors, and token spend for the past 24 hours, and the Stats page tracks users, sessions, events, and total tokens. Cron or one-shot schedules let an agent send a daily brief, and each run is logged. Owner, user, and guest roles control who may talk to an agent or change it, and policy and approval tabs gate risky tool calls. Skills and MCP servers are registered once and enabled for one agent or the whole fleet, and instructions can be pushed to every agent at once. Sessions, memories, and secrets sit in PostgreSQL, so state persists across gateway restarts. Use it for an internal agent platform, a support desk, or one agent per customer. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Give your team one console to build agents, ground them in real data, and reach them through email, Telegram, Slack, and WhatsApp: Huf is a self-hosted multi-agent AI platform running on servers you operate. Create agents visually, assign each one a provider and model, and watch runs, last activity, and status from a grid that shows every agent at a glance; the same console manages prompts, skills, flows, data tables, and knowledge sources. Connect agents to Gmail and email, Telegram, Slack, WhatsApp, and custom HTTP webhooks, and inbound messages trigger runs whose replies route back to the original channel automatically. Agents read, create, update, and delete any Frappe document, work ERPNext data, and call external systems through Model Context Protocol servers with managed OAuth credentials. Code-heavy tasks run in hardened execution profiles: a local Python environment, an isolated venv, direct SSH, a Frappe SSH connection, or a Docker container, each gated by role-based permissions for agents, tools, data tables, and MCP servers. Teams package prompt templates, tools, and MCP configurations into shareable skills and Huf Apps, run models from cloud providers, or keep everything local with Ollama, LM Studio, or any OpenAI-compatible endpoint. 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.