Provides tools for accessing Alibaba Cloud observability products including SLS (Log Service) and ARMS (Application Real-time Monitoring Service), allowing any MCP-compatible AI assistants to quickly interact with these services.

A server monitoring and inspection tool collection that provides remote utilities for checking network interfaces, service statuses, and firewall configurations on servers.

The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.

Provides access to Prometheus metrics and queries through standardized Model Context Protocol interfaces, allowing AI assistants to execute PromQL queries and analyze metrics data.

An MCP interface that allows AI assistants to query and analyze Grafana Loki logs using LogQL, with support for authentication and various output formats.

Server for interacting with Honeycomb observability data. This server enables LLMs like Claude to directly analyze and query your Honeycomb datasets.

Status Observer MCP

for tracing and monitoring

steampipe-mcp

The Seq MCP Server enables interaction with Seq's API endpoints for logging and monitoring, providing tools for managing signals, events, and alerts with extensive filtering and configuration options.

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.

Nessus MCP Server

honeycomb-mcp-server

Get information about the current operating environment

A Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.

Enables interaction with Datadog's monitoring platform to search logs, search trace spans, and perform trace span aggregation for analysis.

Provides access to Consul functionality (services, health checks, KV store, sessions, events, queries, etc.) through a standardized Model Context Protocol interface.

This project provides a Model Context Protocol (MCP) server that allows language models and other MCP clients to interact with a SuzieQ network observability instance via its REST API.

OpsLevel MCP

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

An MCP server for searching and visualizing SolarWinds Observability logs, allowing users to query log data with filtering options and generate visual representations of log events over time.

Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Cloudflare account.

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.

A remote MCP server that enables real-time interaction with the Dynatrace observability platform, bringing production-level monitoring data directly into development workflows.

A Model Context Protocol server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).

A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.

A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.

MCP Server for Raygun's API V3 endpoints for interacting with your Crash Reporting and Real User Monitoring applications. This server provides comprehensive access to Raygun's API features through the Model Context Protocol.

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

A FastMCP-based tool for interacting with Splunk Enterprise/Cloud through natural language. This tool provides a set of capabilities for searching Splunk data, managing KV stores, and accessing Splunk resources

Securely integrates Wazuh security data with LLMs (such as Claude Desktop) by retrieving alerts from Elasticsearch indices and transforming them into MCP-compliant format, enabling real-time security context in LLM applications.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Compute Engine, Cloud Run, Storage, BigQuery, and other GCP services through a standardized MCP interface.

A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

AI-powered assistant that connects Claude to video encoding workflows, translating cryptic errors into plain English and providing actionable solutions for troubleshooting encoding jobs.

An MCP server implementation that enables dynamic configuration of OpenTelemetry Collectors, allowing users to add, remove, and configure receivers, processors, and exporters through MCP tools.

MCP server for interacting with Prometheus metrics and data.

A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.

A Model Context Protocol server that enables LLMs to retrieve and analyze OpenTelemetry traces and metrics from Logfire, supporting exception tracking and custom SQL queries against telemetry data.

This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.

provide access to monitor and cluster logs from datadog

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.

A Model Context Protocol server that performs third-party threat intelligence enrichment for various observables (IP addresses, domains, URLs, emails) using services like VirusTotal, Shodan, and AbuseIPDB.

Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.

Webhook-tester MCP Server

Allows developers and AI Agents to query Google Cloud Logging using natural language, translating queries into Google Cloud Logging Query Language (LQL) with Vertex AI Gemini 2.5.

Facilitates deployment and management of services using the Model Context Protocol with a focus on high availability, scalability, and secure communication, leveraging Docker-based infrastructure, Prometheus, and Grafana for monitoring.

An MCP server that monitors and provides analytics on weekly report submissions in a Google Sheet, allowing users to check missing submissions, view statistics, and track individual reporting status.

A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.

An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.

Integrates with Sumo Logic's API to enable log search with configurable queries and time ranges, supporting error handling and easy deployment via Docker.

A Kubernetes-deployed server for the Model Context Protocol that enables secure communication with configurable environment variables, health monitoring, and scalable deployment on Azure Kubernetes Service.