cacheout-mcp
MCP server for macOS disk cache management. Enables AI agents to free disk space on demand by scanning and clearing developer caches.
README
cacheout-mcp
MCP server for macOS disk cache management — lets AI agents free disk space on demand.
Why
When you run AI agents (OpenClaw, Claude Code, etc.) on a Mac Mini or any macOS machine, disk pressure can silently degrade performance. Swap thrashing, failed builds, Docker OOM — all from running out of space that's locked up in developer caches.
cacheout-mcp gives your agent a set of tools to detect and fix disk pressure in real-time:
Agent detects 2 GB free → calls cacheout_smart_clean(target_gb=15) → 15 GB freed in 3 seconds
Three Execution Modes
| Mode | When | How it works |
|---|---|---|
| Socket | Cacheout daemon running with Unix socket | Connects to daemon for real-time data, trend analysis, health scores |
| App | Cacheout.app installed, no running daemon | Delegates to Cacheout CLI binary (--cli flag) |
| Standalone | No Cacheout.app (headless servers) | Cleans caches directly via Python, reads sysctl for memory stats |
Mode is auto-detected at startup (socket → app → standalone). Override with CACHEOUT_MODE=standalone or CACHEOUT_MODE=app.
Install
# From PyPI (when published)
pip install cacheout-mcp
# From source
cd cacheout-mcp
pip install -e .
MCP Configuration
Claude Code / Claude Desktop
Add to ~/.claude/claude_desktop_config.json or your project's .mcp.json:
{
"mcpServers": {
"cacheout": {
"command": "cacheout-mcp",
"env": {}
}
}
}
OpenClaw / Custom Agents
{
"mcpServers": {
"cacheout": {
"command": "python",
"args": ["-m", "cacheout_mcp.server"],
"env": {
"CACHEOUT_MODE": "standalone"
}
}
}
}
With uv (no install needed)
{
"mcpServers": {
"cacheout": {
"command": "uvx",
"args": ["cacheout-mcp"]
}
}
}
Tools
cacheout_get_disk_usage
Check current disk space. No parameters.
→ {"total": "500.1 GB", "free": "23.4 GB", "used_percent": 95.3}
cacheout_scan_caches
Scan all cache directories and report sizes. Optional filters:
categories: List of slugs to scan (omit for all)min_size_mb: Only show categories above this size
→ {"total_cleanable": "45.2 GB", "categories": [{"slug": "xcode_derived_data", "size_human": "15.0 GB", ...}]}
cacheout_clear_cache
Clear specific categories by slug. Requires explicit category list.
categories: Required list of slugsdry_run: Preview without deleting
← {"categories": ["xcode_derived_data", "homebrew_cache"], "dry_run": false}
→ {"total_freed": "18.2 GB", "results": [...]}
cacheout_smart_clean
The primary tool for agents. Specify how much space you need; it clears safest caches first.
target_gb: Required — how many GB to freedry_run: Preview modeinclude_caution: Include Docker and other high-risk categoriesfree_memory: Also run memory purge after disk cleanup (addsmemory_freed,purge_resultto response)
← {"target_gb": 10.0}
→ {"target_met": true, "total_freed_human": "12.3 GB", "disk_after": {"free_gb": 17.5}}
cacheout_status
Server status, mode, and available categories.
cacheout_get_memory_stats
Check RAM, swap, memory pressure, and memory tier. No parameters.
→ {"total_physical_mb": 16384.0, "memory_tier": "comfortable", "estimated_available_mb": 6096.0, ...}
cacheout_get_process_memory
List top memory-consuming processes. Optional top_n and sort_by parameters.
Returns envelope: {mode, capabilities, data: {processes, count, sort_by_applied}, partial}.
cacheout_get_compressor_health
Check macOS memory compressor ratio, compression/decompression rates, and thrashing detection. No parameters.
Returns envelope: {mode, capabilities, data: {compressor_ratio, thrashing, ...}, partial}.
cacheout_memory_intervention
Run memory interventions. Required parameters:
intervention_name: Canonical name (e.g.,"purge")confirm:falsefor dry-run preview,trueto execute
Returns envelope: {mode, capabilities, data: {dry_run, intervention, ...}, partial}.
cacheout_system_health
Combined disk + memory + alert health check with a 0-100 score. No parameters. In socket mode, fetches from daemon. In standalone, computes locally.
cacheout_check_alerts
Read watchdog alerts (near-zero cost file read). Optional acknowledge parameter.
cacheout_get_recommendations
Get predictive memory/disk recommendations. Socket mode includes trend-based types
(exhaustion_imminent, compressor_degrading). Standalone returns snapshot types only.
cacheout_configure_autopilot
Validate and apply autopilot/watchdog configuration. Required config parameter (dict with
version, enabled, optional rules/webhook/telegram). This is a write/validate/apply tool.
Cache Categories (23 total)
| Slug | Risk | What it cleans |
|---|---|---|
xcode_derived_data |
Safe | Build artifacts, indexes |
uv_cache |
Safe | Fast Python installer cache |
homebrew_cache |
Safe | Downloaded bottles/tarballs |
npm_cache |
Safe | npm package cache |
yarn_cache |
Safe | Yarn package cache |
pnpm_store |
Safe | pnpm content-addressable store |
bun_cache |
Safe | Bun package manager cache |
typescript_cache |
Safe | TypeScript compiler + Next.js SWC cache |
playwright_browsers |
Safe | Playwright browser binaries |
cocoapods_cache |
Safe | CocoaPods specs and pods |
node_gyp_cache |
Safe | Native Node.js addon headers |
prisma_engines |
Safe | Prisma ORM query engine binaries |
swift_pm_cache |
Safe | Swift Package Manager cache |
gradle_cache |
Safe | Gradle build cache |
pip_cache |
Safe | Python pip cache |
chatgpt_desktop_cache |
Safe | ChatGPT desktop app cache |
vscode_cache |
Safe | VS Code updates and extensions |
electron_cache |
Safe | Shared Electron framework cache |
browser_caches |
Review | Brave/Chrome cached web content |
xcode_device_support |
Review | iOS device debug symbols |
simulator_devices |
Review | iOS/watchOS simulator data (uses xcrun) |
torch_hub |
Review | PyTorch models (slow to re-download) |
docker_disk |
Caution | Docker virtual disk (all images/containers) |
Smart Clean Priority
When smart_clean is called, categories are cleaned in this order:
- Safe categories, sorted by clean_priority (build artifacts first)
- Review categories (browser caches, device support)
- Caution categories (Docker) — only if
include_caution=true
Stops as soon as target_gb is freed.
Environment Variables
| Variable | Default | Description |
|---|---|---|
CACHEOUT_MODE |
auto-detect | Force standalone or app mode |
CACHEOUT_BIN |
auto-detect | Path to Cacheout binary |
Adding the CLI to Cacheout.app
If you maintain the Cacheout Swift app, add the CLIHandler.swift file to your Sources
and update CacheoutApp.swift to check CLIHandler.shouldHandleCLI() on init.
This enables Cacheout --cli scan, Cacheout --cli clean, etc. for app-mode integration.
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。