"WP Rocket" matching MCP servers:

Enables an AI assistant to diagnose a local WordPress install by listing plugins, checking PHP/WP environment, tailing debug logs, running guarded read-only SQL queries, and inspecting Gravity Forms error and add-on logs.

Enables MCP-capable LLM clients to perform read-only Linux system observation and OS algorithm experiments by exposing typed tools for memory, filesystem, process, and CPU scheduling data with controlled, safe boundaries.

Exposes a Raspberry Pi homelab's systemd service health, disk usage, CPU temperature, and LAN game-server status as read-only MCP tools, letting MCP clients answer questions like "how's the homelab doing?" without SSHing in manually.

Enables AI assistants to query IP Fabric network inventory and snapshots through natural language, using tools to fetch devices, interfaces, routing tables, and more.

MCP server analyzing Windows ETW (.etl) traces — 54 tools spanning CPU/wait stacks, image-load gaps, file/disk/mmap I/O, VirtualAlloc, network, registry, ALPC, DPC/ISR, CLR (GC/JIT/alloc/exception/contention), NT heap, and any user-mode ETW provider. Domain-neutral; works on any Windows trace.

Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.

Read-only MCP server for Elasticsearch log querying. Enables natural language search, filtering, context retrieval, and aggregation of logs.

Enables SafeOps operators to monitor worker health, inspect job queues, investigate incidents, search runbooks, and approve or reject targeted failed-job retries through MCP tools, resources, and a prompt.

MCP server that exposes WebSocket session management as tools, allowing AI agents to open persistent connections, send typed frames, drain buffered messages, and monitor per-frame Shannon entropy to detect schema divergence.

Enables AI assistants to query real-time system metrics like CPU, RAM, disk, and battery usage, and check performance thresholds.