"A server for Linux file operations" matching MCP servers:

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

Enables read-only access to operations and telemetry data across 12 domains through 45 agent tools, including asset inventory, metrics, outages, incidents, and platform settings, with support for AWS SigV4-signed live access and a fixture-based mock mode that runs without a backend.

Self-hosted Linux administration over MCP: 38 tools for processes, disks, network, systemd, journal and files, served over HTTPS. Each call runs as the caller's own OS user; root is granted per tool, limited to paths, networks and sysctl keys.

A comprehensive Linux system performance profiler with MCP remote invocation support, featuring advanced process profiling and flame graph generation.

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

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

Enables secure, read-only inspection of a VPS over SSH through approved operations such as system health, disk usage, container logs, and service status, without giving the AI unrestricted shell access.

A Model Context Protocol (MCP) server that exposes 48 tools covering the full spectrum of iSuite enterprise administration — user management, role verification, job monitoring, scheduler control, batch execution, audit trail lookup, and configuration validation.

An MCP-native enterprise operations platform that unifies team management, product catalog, order processing, knowledge base, location intelligence, analytics, and DevOps monitoring into a single server accessible from any MCP-compatible AI agent.

Enables cloud and platform engineers to investigate AWS incidents by grounding responses in approved runbooks and operational evidence, with authenticated access, citations, observability, and human approval before any write action.

Enables AI assistants to read and analyze Linux system logs—including systemd journal, syslog, kernel, application, and Docker container logs—for diagnostics and predictive analysis.

A safe, read-only MCP server that gives Codex structured access to engineering operations evidence, with validated queries, secret redaction, and audit logging. Provides a search_logs tool for filtering logs by service, environment, severity, and time range.

A read-only MCP server that lets an AI assistant inspect a single AWS lab instance's EC2 health, recent system/nginx errors from CloudWatch, and nginx service status via SSM, with strict allowlisting and no generic shell access.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables AI agents to diagnose Linux server incidents by collecting and structuring system diagnostics from multiple servers via SSH, with tools for finding incident clusters, gathering context (memory, CPU, swap, etc.), and running arbitrary commands.