"A server for test coverage and MCP integration" matching MCP servers:

Enables read-only monitoring, failed-message analysis, health summarization, and AI-assisted troubleshooting against SAP Cloud Integration tenants through MCP-compatible clients.

Enables an LLM assistant to analyze automated test results, search logs, group failures by cause, and draft Jira bugs with steps to reproduce, with dry-run Jira filing by default.

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.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

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.

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.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

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 models to query and analyze Kubernetes cluster logs through Grafana Loki, supporting semantic operations like error aggregation and pod restart detection. It provides tools for regex-based log searching and namespace discovery to facilitate natural language troubleshooting.

An MCP server that connects language models to a Wazuh SIEM cluster, enabling read-only plain-language queries, schema inspection, field coverage analysis, and decoder testing.

A read-only MCP server for the Logitech Sync Cloud API, providing tools to inspect rooms, desks, devices, health, occupancy, coverage, environmental readings, and network information.

Enables AI-assisted analysis of log files through advanced searching, filtering, and test execution capabilities. Supports time-based queries, pattern matching, test summarization, and code coverage reporting directly within compatible MCP clients.

A comprehensive read-only MCP server for Datadog, providing 117 tools to query logs, APM, metrics, monitors, dashboards, SLOs, and more, with zero write capabilities for safe AI integration.

Connect engineering metrics, DORA performance, deploy risk scoring, and PR health to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.

A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.

Enables Windows event log forensics by wrapping Hayabusa, offering EVTX scanning, Sigma rule exploration, ATT&CK coverage analysis, and detection engineering resources.

Hosted remote MCP server for issuing run receipts, summarizing agent changes, checking test evidence, flagging review risks, and exporting run logs for Antigravity agents.