"A system for managing project to-do lists with change logging" matching MCP servers:

MCP server for embedded board debugging, providing structured serial capture, crash decoding, and flash-safe port arbitration via bounded CLI and MCP tools.

Provides comprehensive logging and monitoring capabilities for MCP services with real-time log tailing, advanced search, error analysis, and anomaly detection. Enables centralized log aggregation, correlation tracking, and health monitoring across all MCP ecosystem services.

A template for deploying MCP servers as Cloudflare Workers with integrated LogPush and R2 storage for detailed execution logging. It enables remote tool execution and provides utilities for retrieving logs directly from Cloudflare R2 buckets.

Enables monitoring of Ubuntu system metrics, Docker containers, and public IP drift, with Feishu alerting and HTTP/MCP tools for querying status, viewing history, and restarting containers.

Enables AI assistants to query, search, and analyze logs across Google Cloud Platform projects. It supports advanced filtering by severity or resource type and provides detailed log entry retrieval and project listing capabilities.

Enables querying ShareFile OpenSearch production logs via MCP with automatic EntraID OAuth authentication.

An MCP server that enables interaction with Google Cloud Logging API, allowing users to write, read, and manage log entries and configurations through natural language.

Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

Read-only MCP server for observing Linux hosts (systemd, ZFS, Docker, VMs, network, hardware, NixOS) as a graph of objects with provenance. Provides seven tools to list hosts, get status, collections, objects, evidence, lookup, and changes.

Enables AI clients to access real-time system information such as memory and swap usage from a Linux machine via MCP tools.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Provides a read-only summary of Ubuntu server status including system version, resource usage, apt updates, service health, security logs, and hardware information to AI clients via MCP tools.

Enables LLMs to monitor system health, manage processes, execute shell commands, and inspect environment variables and directories.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.

Provides AI agents with tools to retrieve live system statistics (CPU, memory) and safely evaluate basic arithmetic expressions.

Provides real-time Linux system monitoring for CPU load, memory usage, disk space, and process activity. This server enables users to retrieve comprehensive performance metrics and resource utilization data through a standardized interface.

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.