Gargantua

data-ai MCP Server

Native macOS system cleaner with YAML-driven safety rules, local AI explainability via MLX, and an MCP server for agent-controlled cleanup workflows.

Verified
data-aidata-ai
4 views50 stars4 forksAGPL-3.0

Why This Matters

Discovered via github-topic:model-context-protocol and last synced 3mo ago.

Verified
Source
github-topic:model-context-protocol
Stars
50
Last synced
3mo ago
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16
Tools
0
Resources
0
Prompts
Standard I/O
Transport

Available Tools (16)

safe

Disposable files that are expected to regenerate or have no user-owned state.

Level

Meaning

review

Files that may be removable, but could contain preferences, sync state, offline data, or context the user should inspect.

protected

Files with system impact, privilege implications, or high risk of data loss.

confirm: true

is required.

explain

explain a filesystem path or prior scan item

Unknown

item IDs are rejected.

scan

dry-run scan for reclaimable items

Each

MCP client gets one clean operation per 60 seconds.

clean

clean item IDs returned by a prior `scan`

list_profiles

list built-in and custom cleanup profiles

Any

`protected` item aborts the whole request.

status

current system health metrics

The

app attempts a local notification with a short cancel window before files move.

analyze

health score, disk usage, and recommendations

Every

non-dry-run attempt writes an audit entry with the client identifier to `~/Library/Logs/Gargantua/audit.json`.