Core concepts

Eggent is built like an employee's desk. Below is every concept you will meet in the interface and in these docs. If you read one page from start to finish, make it this one.

#Workspace

A workspace is your whole Eggent: one computer for the agent, with all its projects, files, chats and settings. In the cloud every workspace has its own address, name.cloud.eggent.ai. On your own server the workspace is the ./data folder.

Everything the agent does happens inside the workspace. It cannot see other workspaces, and nobody else can see yours.

#Orchestrator

The orchestrator is the agent that answers when no project is selected. It is the workspace's main conversation: good for anything at all, and it knows which projects exist, so it can switch into the right one by itself.

The orchestrator has its own context, memory, skills and MCP servers, separate from the projects. Its model is always the workspace model.

#Project

A project is a separate desk for one job or area: "Website", "Sales", "Channel content". Every project has its own:

• files (the project folder);
• context — standing instructions for the agent;
• memory;
• skills;
• MCP servers;
• optionally, its own model.

When a project is selected, the agent works in its folder and sees only its settings, so instructions for the website do not get in the way of a conversation about accounting. From any chat you can also hand a task to a project by writing @ and its name. More in Projects and the orchestrator.

#Chat

A chat is one conversation with the agent. A chat belongs to the project it was started in, or to the orchestrator. Every chat has its own address and can be opened from a link, in another tab or from your phone. The work in a chat keeps going if you close the tab. See Chats.

#Context

Context is the standing instructions the agent receives with every message: who you are, how to answer, what matters in this project. It lives in context.md — one for the orchestrator and one per project. See Context.

#Memory

Memory is what the agent wrote down to remember between chats: facts, decisions, preferences. It lives in memory.md. The agent searches it when needed, and you can ask it to remember or forget something. The agent also keeps a few short notes about you and the work by itself, and reads them in every chat. See Memory.

#Skill

A skill is a ready-made instruction for one kind of work: how to run a knowledge base, how to write articles for a site, how to fill documents from a template. A skill is a folder with a SKILL.md file and, if needed, scripts. The agent picks up the right skill when it sees the task the skill was written for. See Skills and Skill catalog.

#MCP

MCP (Model Context Protocol) is the standard way to connect an external service to the agent: spreadsheets, a CRM, social networks, databases. A connected MCP server gives the agent new tools. See MCP.

#Model

The model is the language model that thinks and writes for the agent. The cloud comes with Eggent AI connected — a set of models from several families, paid for from the workspace balance. You can also connect your own key from any provider. The model is chosen for the whole workspace and, separately, per project. See Models.

#Schedule

A schedule is a task the agent runs by itself at a given time: every day at 9:00, every hour, in 10 minutes. You create one by asking in chat, and the result arrives in the same chat or in Telegram. See Schedules.

#Board

The board is where work is handed to the agent as cards. Each card is a task the agent carries out by itself in a conversation of its own, one after another; a card can wait for others and start with what they came to: "collect → compare → summarise". See Task board.

#How it fits together

Workspace (name.cloud.eggent.ai or ./data)
├── Orchestrator ─ context, memory, skills, MCP
│   └── chats without a project
├── Project "Website" ─ files, context, memory, skills, MCP, model
│   └── project chats
├── Project "Sales" ─ …
├── Schedules ─ live in the chats that created them
└── Settings ─ models, Telegram, API

A simple rule: keep everything that belongs to one job in one project. The agent in a project sees its files, instructions and memory, so you do not have to explain it all again every time.