feat: add comprehensive documentation for AI Workspace, including architecture, memory model, profiles, services, and security guidelines
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# MCP Integration
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The Model Context Protocol (MCP) is the workspace's standard interface for exposing local context to AI clients.
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## Role In AI Workspace
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`aiw-context-mcp` is a read-only context server. It exposes bounded profile context through MCP tools and resources.
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It should not:
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- capture communication traffic;
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- send messages;
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- write canonical memory;
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- promote facts automatically;
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- expose secrets or raw credentials.
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## MCP Concepts
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MCP uses a host/client/server model:
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- **Host**: the AI app, such as OpenCode, Claude Code, VS Code, Copilot, or another client.
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- **Client**: the connection the host opens to a server.
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- **Server**: a local or remote program that exposes context.
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Servers expose primitives such as:
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- **Tools**: callable functions.
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- **Resources**: readable context objects.
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- **Prompts**: reusable prompt templates.
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AI Workspace currently focuses on tools and resources.
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## Current Tools
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Examples:
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- `context_profiles`
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- `project_current_context`
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- `project_search_memory`
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- `memory_hybrid_search`
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- `communication_latest`
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- `communication_date_context`
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- `communication_standup_context`
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- `photos_latest`
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## Current Resources
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Examples:
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```text
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aiw://profiles/fidelity/current-work
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aiw://profiles/fidelity/work-items
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aiw://profiles/fidelity/mattermost/latest
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aiw://profiles/fidelity/photos/latest
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```
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## Security Posture
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MCP tools can be model-controlled in many clients, so this workspace defaults to read-only context tools. If write tools are added later, they should require clear user intent, narrow scope, and audit-friendly outputs.
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## Start The MCP Server
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HTTP transport:
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```bash
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python3 scripts/aiw/services.py start aiw-context-mcp --profile fidelity
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```
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stdio transport:
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```bash
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python3 scripts/mcp/aiw-context-mcp/server.py --transport stdio
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```
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