# MCP Integration

The Model Context Protocol (MCP) is the workspace's standard interface for exposing local context to AI clients.

## Role In AI Workspace

`aiw-context-mcp` is a read-only context server. It exposes bounded profile context through MCP tools and resources.

It should not:

- capture communication traffic;
- send messages;
- write canonical memory;
- promote facts automatically;
- expose secrets or raw credentials.

## MCP Concepts

MCP uses a host/client/server model:

- **Host**: the AI app, such as OpenCode, Claude Code, VS Code, Copilot, or another client.
- **Client**: the connection the host opens to a server.
- **Server**: a local or remote program that exposes context.

Servers expose primitives such as:

- **Tools**: callable functions.
- **Resources**: readable context objects.
- **Prompts**: reusable prompt templates.

AI Workspace currently focuses on tools and resources.

## Current Tools

Examples:

- `context_profiles`
- `project_current_context`
- `project_search_memory`
- `memory_hybrid_search`
- `communication_latest`
- `communication_date_context`
- `communication_standup_context`
- `photos_latest`

## Current Resources

Examples:

```text
aiw://profiles/fidelity/current-work
aiw://profiles/fidelity/work-items
aiw://profiles/fidelity/mattermost/latest
aiw://profiles/fidelity/photos/latest
```

## Security Posture

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.

## Start The MCP Server

HTTP transport:

```bash
python3 scripts/aiw/services.py start aiw-context-mcp --profile fidelity
```

stdio transport:

```bash
python3 scripts/mcp/aiw-context-mcp/server.py --transport stdio
```