"Support resources for HTTP-related issues or questions" matching MCP servers:

A read-only MCP server exposing SLURM, GPFS, Prometheus (node exporter + DCGM GPU metrics) and generic Elasticsearch exploration as diagnostic tools for LLM-based HPC support assistants.

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

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.

stateless MCP server — fresh instance per request, infinite horizontal scaling

Connects AI assistants to live VuNet observability data, allowing querying metrics, browsing data models, and checking connection status.

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 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.

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

Provides tools to search Splunk logs, inject test data, and send triage emails, enabling AI-driven incident investigation.

Provides Model Context Protocol access to the Dynatrace platform API, letting AI agents run live queries against observability, security, and platform data and manage a Dynatrace environment. It is hosted remotely by Dynatrace, so MCP hosts can add it by name from the official registry without installing anything.

A remote, Dynatrace-hosted MCP server that gives AI agents live API access to your Dynatrace environment. It enables querying and analyzing observability, security, and platform data — such as DQL queries, logs, traces, problems, and dashboards — so agents can act on production context instead of static knowledge.

Enables AI agents to check the health of internet infrastructure and specific services, helping diagnose whether issues are local or external.

Lets an AI assistant answer performance questions from Tideways data by reading projects, metrics, issues and traces through the read-only REST API.

Enables agents to interact with a GlitchTip instance for issues, events, projects, releases, alerts, uptime monitors, performance, and more via stdio or HTTP.

Enables diagnosing web hosting and server issues by running live HTTP, SSL, DNS, and security-header checks alongside a searchable troubleshooting knowledge base.

Cross-cloud observability for AI agents. Discover resources, correlate logs, and diagnose infrastructure issues across AWS, GCP, Vercel, and Cloudflare — without leaving your editor.

Connect AI assistants to Sentry for error tracking, issues, releases, events, and project management through the Model Context Protocol. Provides tools to list organizations, projects, issues, events, releases, teams, and members, as well as get details and update issue status.

An MCP server with bearer token authentication implementing tools, resources, and prompts for a mock developer platform API, supporting both stdio and Streamable HTTP transports.

Enables observation-only system inspection through MCP, exposing system identity, resources, process summary, and network summary without any mutation or command execution.

A production-ready TypeScript template for building MCP servers with dual transport support (stdio/HTTP), OAuth 2.1 foundations, SQLite caching, observability, and security features including PII sanitization and rate limiting.

Provides MCP resources and tools that expose runtime JVM process info, startup flags, properties, and consolidated thread dumps with deadlock detection so an LLM can diagnose live JVM issues.

Enables MCP-aware AI agents to query the local machine's health over stdio, retrieving CPU, memory, disk, and load-average metrics along with boot time and the top processes by CPU usage. It gives coding agents a structured, protocol-standard way to answer questions like whether it is safe to run a build or what is currently consuming resources.

Enables endpoint availability monitoring and HTTP health checks for single or multiple URLs.

Enables management of Lucky 3.0 via MCP, providing tools for reverse proxy, certificates, port forwarding, DDNS, and related modules using OpenToken authentication.

A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.

Bugfender MCP server for read access to logs, devices, crashes, and issues, with automatic token refresh.