"Windows Performance Toolkit and xperf.exe" matching MCP servers:

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.

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 exposes core Azure services as read-mostly tools any MCP client can call, including Blob Storage, Key Vault, Service Bus, and Resource Manager.

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.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

A deployable MCP server template for Cloudflare Workers that provides Google OAuth authentication and comprehensive analytics tracking of tool usage, performance metrics, and user behavior.

Stateless Streamable HTTP MCP endpoint with OAuth 2.1 authentication via Cloudflare Workers, supporting PKCE, DCR, and token introspection.

Bridges AI IDEs with Tencent CloudBase for seamless deployment, enabling users to go from AI-generated code to live applications with automatic cloud resource configuration, database setup, and intelligent debugging.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Talk to your SaaS tools including HubSpot, Salesforce, and more

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables natural-language querying and analysis of AWS spending and model-invocation usage, including detailed breakdowns by service, region, account, day, and instance type.

Enables natural-language queries of AWS spend and Bedrock usage data, providing detailed breakdowns by service, region, account, user, instance type, and model, including cross-account cost analysis.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.

Enables natural-language analysis of AWS spend through Cost Explorer and Amazon Bedrock usage via CloudWatch model invocation logs, with breakdowns by service, region, model, user, day, and instance type. It also supports cross-account cost retrieval and local or remote MCP transports.

Enables users to query AWS spend data and Amazon Bedrock usage from CloudWatch model invocation logs through natural language. Supports detailed cost breakdowns by service, region, day, and instance type, including cross-account AWS spend retrieval.

Enables users to query AWS spending and Amazon Bedrock usage in natural language through MCP clients, with breakdowns by service, region, day, model, and user, plus optional cross-account access.

Enables users to query and analyze cloud spending, EC2 cost breakdowns, service-level spend, and model usage logs through natural-language interactions. It also supports cross-account spend retrieval when configured.

Enables agents to retrieve and analyze cloud spending and model usage data, including service, region, instance-type, user, and model breakdowns.

Enables querying AWS Cost Explorer spend data and Amazon Bedrock model invocation logs through CloudWatch in natural language. Supports EC2, Bedrock, and cross-account cost analysis via local or remote MCP transports.

Enables querying AWS spend data via Cost Explorer and Amazon Bedrock usage data from CloudWatch logs using natural language. Supports cross-account access, local and remote deployment, and integration with Claude Desktop and LangGraph agents.

Enables users to analyze AWS spend and Bedrock model usage through natural-language queries, including EC2 costs, service spend reports, and breakdowns by region, model, and user.

Enables users to query AWS Cost Explorer spend data and Amazon Bedrock usage data from CloudWatch model invocation logs through natural language, including EC2 breakdowns, service spend reports, and detailed cost data by day, region, service, and instance type.

Enables AI assistants to interact with Fastly's CDN API through the Model Context Protocol, allowing secure management of CDN services, caching, security settings, and performance monitoring without exposing API keys.

A Model Context Protocol server that allows AI models to access, analyze, and manage Meta advertising campaigns, enabling LLMs to retrieve performance data, visualize ad creatives, and provide strategic insights for Facebook and Instagram platforms.

Enables AI agents to design cloud architectures, run cost/performance simulations, and draw them on a Pinpole canvas directly from Claude Code, Cursor, and OpenAI Codex.

Enables real-time monitoring of F5 Cloud service status, including 148+ service components, active incidents, and scheduled maintenance windows with intelligent caching and dual data source reliability.

Enterprise-grade Azure security assessment toolkit with multi-location scanning, IMDS exploitation, attack path analysis, and compliance reporting. Enables authorized penetration testing and compliance audits across all Azure regions.

MCP server that integrates with Coolify to let AI assistants manage Coolify instances via a clean toolkit wrapping the official REST API.