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

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.

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.

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.

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.

Enables MCP clients to inspect Oracle Integration Cloud integrations, connections, runtime instances, errors, and flow logs through natural-language queries.

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.

Enables LLM clients to query AWS CloudWatch Logs and Alarms through MCP tools.

Enables enterprise-managed authorization for MCP on Azure App Service, with deployable Entra OAuth and a local EMA ID-JAG lab exposing whoami and authorization_model tools.

A Model Context Protocol server that enables Claude to execute SQL queries on Snowflake databases with automatic connection lifecycle management.

Provides GPU-accelerated gradient boosting model training and inference through a cloud service. Enables AI agents to train models on NVIDIA A10G GPUs and get fast cached predictions with portable model artifacts.

Enables authenticated HTTP MCP clients to call a bounded, read-only tool that counts Unicode code points in supplied text without accessing files, networks, or application state.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

An MCP server that provides access to Google's API Discovery Service, allowing agents to discover and interact with Google APIs through natural language commands.

An MCP Server that enables interaction with Google's Service Usage API, allowing management and control of which Google Cloud Platform APIs and services are enabled for a project.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Enables AI agents to query Oracle Integration Cloud read-only across multiple environments in plain language, covering integrations, runtime instances, errors, schedules, connections and flow design through 36 GET-based tools.

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

A hardened MCP server that enforces authentication via Easy Auth and OAuth, manages secrets with Key Vault, and restricts network access using VNet integration and API Management, enabling secure tool invocations through a fully private infrastructure.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

A Model Context Protocol server that provides access to Snowflake databases for any MCP-compatible client, allowing execution of SQL queries with automatic connection management.

Enables a stateless, horizontally scaled MCP server using the 2026-07-28 specification, with tools for load testing and instance-aware operations.

Enables natural language-powered ETL workflows using Airflow, AWS Glue, Athena, and S3, allowing LLM agents to control and monitor data infrastructure.

Provides read-only access to Umbrella Cost finops platform, enabling natural language querying of multi-cloud cost data, optimization recommendations, anomaly detection, and budget tracking across AWS, Azure, and GCP.

MCP server for Azure Service Bus that enables sending messages, inspecting queues and subscriptions, and purging test data. Complements the built-in Azure MCP server by adding write operations.

Connects AI tools to BlazeMeter's Service Virtualization platform, enabling natural language management of virtual services, transactions, and configurations.

Enables AI assistants to run engineering simulations on cloudHPC, including inspecting cases, getting resource advice, uploading, launching, monitoring, diagnosing errors, and downloading results.