"Using Git with Python for Operations" matching MCP servers:

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.

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.

MCP server for safely exposing SQL Server database capabilities to LLM clients, with read-only mode, security features, and observability.

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of systems using Langfuse.

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.

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.

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.

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 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 (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.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

A comprehensive network management platform for tracking devices, sites, and topologies across platforms like ZeroTier and UniFi. It enables automated device discovery, multi-hop access path visualization, and infrastructure troubleshooting through the Model Context Protocol.

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.

Asynchronous MCP server for unified multi-platform network infrastructure management, providing 97 tools across 10 connectors including SSH, MikroTik, Palo Alto, Aruba, Graylog, LibreNMS, Cisco APIC/NDFC, and Panorama.

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

An MCP server for Prometheus-based monitoring that enables users to query system metrics, resource usage, and PostgreSQL health across multiple environments. It supports both predefined diagnostic checks and custom PromQL execution for comprehensive server monitoring and troubleshooting.

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.