"A service for application performance monitoring and observability" matching MCP servers:

Unified observability gateway for AI agents — one MCP server for Prometheus, Loki, and any backend.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

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.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

An MCP server that enables querying performance review periods, records, details, and saving self-assessment drafts without final submission.

Governs and automates network monitoring across SolarWinds Orion and Paessler PRTG platforms with a unified MCP server, enabling querying, alert management, and governed writes with audit logging.

MCP server for monitoring, diagnosing, and auto-correcting observability issues across platform services, integrating with Sentry and PostgreSQL for error tracking and billing pipeline health.

Unified MCP server for observability and monitoring, providing tools to query metrics, logs, and traces through Prometheus, Grafana, Loki, and Jaeger.

MCP server for querying observability data from Elasticsearch, SkyWalking, and Prometheus/VictoriaMetrics, enabling AI models to search logs, traces, and metrics across environments.

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.

AutomateLab SEO Performance combines search and analytics data into clear actions for each URL. Find content to refresh and track results from your MCP client. Product and documentation: https://automatelab.tech/products/mcp/seo-performance-mcp/

A comprehensive Model Context Protocol (MCP) server for Grafana, Prometheus, Kafka UI, and Datadog. Features a secure "Bring Your Own Key" (BYOK) architecture where credentials stay local. Provides tools for metrics querying, dashboard inspection, Kafka lag monitoring, and unified health checks.

Governed Prometheus + Grafana operations — firing-alert and scrape-target RCA, alert noise/flapping analysis, silences, and dashboards, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Connects AI agents to live observability stacks including Sentry, GitHub, Vercel, Better Stack, and Cloudflare, enabling end-to-end incident investigation, deployment correlation, root cause analysis, and regression triage.

Enables comprehensive analysis of AWS Lambda performance including cold start tracking, memory utilization monitoring, cost analysis, and optimization recommendations. Provides real-time metrics, comparative analysis across multiple functions, and actionable insights to improve Lambda performance and reduce costs.

Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.

Enables developers to investigate request failures by querying Prometheus metrics, Loki logs, and Tempo traces without opening Grafana, while supporting read-only access and optional Grafana annotations.

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.

Provides AI assistants with direct access to Red Hat OpenShift AI observability data, enabling querying of Prometheus metrics, Alertmanager alerts, Loki logs, Grafana dashboards, and Kubernetes cluster state to troubleshoot vLLM inference workloads.

Generates formatted performance review documents by providing employee details, review period, accomplishments, and improvement areas.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Provides Claude AI assistants with focused monitoring tools for n8n workflow execution analysis, including active workflow listing, execution history with KPIs, and detailed failure information.

Enables MCP clients to query seeded logs, latency/error-rate metrics, and alerts for five fictional microservices over a remote StreamableHTTP endpoint, with bearer-token access control.

An MCP server that provides access to Google Cloud Monitoring API, enabling interaction with cloud resources monitoring data through natural language commands.

Enables Managed Agent sessions to retrieve provider-specific alarms, metrics, and logs through MCP tools, supporting mock and AWS-backed monitoring data.

A Python-based MCP server that analyzes PostgreSQL query plans, suggests indexes, and checks pagination safety to help optimize database performance.

Enables Claude Web users to manage their job application workflow by storing profile and resume data, analyzing job descriptions, preparing applications, and tracking progress — all with manual submission and no platform automation.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

A minimal Model Context Protocol (MCP) service for integration with external platforms. Provides CRUD operations, reference data fetching, and authentication capabilities.