# AIWorkspace Overview

AIWorkspace helps developers give AI tools the right project context at the right time.

It is designed for teams and individuals who use multiple AI clients—OpenCode, GitHub Copilot, Claude Code, Cursor, VS Code, or others—but do not want project knowledge scattered across chat histories, prompt files, and product repositories.

## What AIWorkspace Does

AIWorkspace provides a local platform to:

- connect communication and evidence sources;
- keep canonical project memory in human-readable Markdown;
- index that memory for fast retrieval;
- expose bounded context through MCP;
- generate AI client configuration when needed;
- run local services such as context servers, capture proxies, and inbox receivers;
- keep raw evidence separate from curated project knowledge.

## What AIWorkspace Is Not

AIWorkspace is not:

- a replacement for a product repository;
- a replacement for project documentation;
- a cloud memory system;
- a single-agent framework that forces one AI workflow;
- a place to store secrets in Git;
- a dumping ground for raw chat exports.

## Target User Flow

```text
Developer installs AIWorkspace
        ↓
Registers or creates a project context pack
        ↓
Connects evidence sources and local repos
        ↓
AIWorkspace captures evidence and maintains indexes
        ↓
AI clients ask AIWorkspace MCP for project context
        ↓
Humans and agents update canonical project memory
```

## Key Concepts

| Concept | Meaning |
|---|---|
| AIWorkspace Core | The reusable app, CLI, scripts, MCP server, connectors, templates, and documentation. |
| User Registry | Local app configuration that remembers registered projects, paths, preferences, and service state. |
| Project Context Pack | A project-specific folder or repo containing canonical memory, connector config, prompts, and optional raw evidence. |
| Canonical Memory | Human-readable Markdown that represents current durable project knowledge. |
| Raw Evidence | Captured messages, screenshots, exports, logs, or documents before curation. |
| AI Client | Any tool that consumes context: OpenCode, Copilot, Claude Code, Cursor, VS Code, etc. |

## Design Goal

AIWorkspace should be plug-and-play for a new developer:

1. install the app and CLI;
2. register an existing context pack or create a new one;
3. connect sources such as Mattermost, Slack, tickets, email, calendar, or local folders;
4. let AIWorkspace detect repositories and services;
5. use any AI client with project-aware context through MCP.