SysFlow MCP
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- AlicenseNot gradedqualityCmaintenanceLets an AI assistant inspect a Linux machine through ten fixed read-only tools covering load, memory, disks, processes, ports, interfaces, systemd units, the journal, and allowlisted log files. All output is size-capped, control-character-stripped and secret-redacted, and nothing in the package can write to the system.MIT
- AlicenseAqualityCmaintenanceProvides read-only access to host system metrics (CPU, memory, disk), Docker container health/logs, and sandboxed log file analysis via MCP tools, enabling AI agents to monitor enterprise infrastructure safely.3MIT
- AlicenseAqualityDmaintenanceEnables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.292GPL 2.0
- AlicenseAqualityDmaintenanceEnables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.10MIT
- AlicenseAqualityBmaintenanceEnables AI agents to safely monitor Linux VPS health, inspect Docker containers, retrieve service logs, and execute whitelisted recovery actions via MCP.31391 npm305 PyPIMIT
- AlicenseNot gradedqualityNot gradedmaintenanceProvides AI assistants with safe, read-only access to Linux systemd services, including status monitoring, log querying, and dependency analysis, with optional granular permissions for service management actions.2-
TDQS
Scored across 4 tools
Each tool targets a clearly distinct area: system resources, log tailing, systemd services, and systemd timers. The service and timer tools are related but their descriptions make the boundary explicit.
All tool names follow a consistent snake_case verb_noun pattern: check_system_resources, tail_logs, inspect_systemd_services, inspect_systemd_timers. There are no mixed conventions or vague standalone verbs.
Four tools are focused and each has a clear purpose, but the set is somewhat thin for a general system diagnostics server. Additional common operations could reasonably be expected.
Core diagnostic areas are covered: resources, logs, services, and timers. Minor gaps exist around process listing, network status, or journal-specific queries, but agents can work around them with the provided tools.