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206,281 tools. Last updated 2026-06-17 11:16

"MCP tools for monitoring application memory and CPU usage" matching MCP tools:

Matching MCP Servers

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    Enables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.
    Last updated
    18
    MIT
  • A
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
    Last updated
    40
    1
    Apache 2.0

Matching MCP Connectors

  • One memory, every AI. A shared, user-owned markdown memory your AI clients read and write over MCP.

  • AI memory with 56 tools. Knowledge Graph, semantic search, OAuth 2.1 + Magic Link. Free tier.

  • Diagnose system performance by retrieving a complete health snapshot including CPU, memory, swap, disk, and uptime.
    MIT
  • Consolidates application-specific help and introspection operations into one tool. List tools, get tool info, schemas, or general help about virtualization-mcp.
    MIT
  • Retrieves live CPU/memory usage for Kubernetes pods, workloads, or nodes, ranked by resource consumption to pinpoint high-utilization components causing performance issues.
    Apache 2.0
  • Retrieve current server environment details including operating system, Node.js version, process info, CPU, memory usage, and hostname.
    MIT
  • Retrieve comprehensive instructions for using the Memory Bank MCP server. Call at the start of every session to understand available tools and the recommended workflow for persistent memory storage.
    MIT
  • Retrieve system details including OS, CPU, memory, disk usage, uptime, and hostname. Use this to assess resources or diagnose environment issues.
    MIT
  • Retrieve real-time cluster status and load distribution per node, including CPU, memory, load average, active tasks, health, and reachability, to monitor health and determine optimal routing.
    MIT
  • Modify server resource limits and feature caps including memory, CPU, disk, swap, IO weight, and database/backup allocations. Changes apply after server restart.
  • Access documentation and usage guides for n8n workflow automation tools to understand available capabilities and implementation methods.
    MIT