"Building and Deploying a React Application with Docker and a Postgres Backend" matching MCP servers:

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

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 AI agents to read Microsoft Fabric lakehouse or warehouse tables, infer keys and relationships, and create or update a GraphQL API item — returning a ready endpoint for Lovable, Cursor, or Claude Code. It also plans and validates schemas and drafts companion artifacts such as semantic models, dbt sources, join paths, and data dictionaries, with dry-run defaults.

Enables LLMs to search Docker Hub repositories, discover container images, and manage Docker Hub repositories and tags through natural language queries. Supports both public content access and authenticated operations with Docker Personal Access Tokens.

Enables AI assistants to search, analyze, and manage Docker images on Docker Hub through standardized MCP tools, with features including security scanning, layer analysis, and image comparison.

A comprehensive MCP server that provides advanced Docker operations through a unified interface with 16 MCP tools and 25+ CLI aliases, enabling secure container lifecycle management, multi-container orchestration, registry publishing, and system maintenance.

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.

MCP server for querying Docker Hub image statistics, including pull counts, stars, descriptions, and publisher catalogs. No API key required.

Provides tools for managing Docker containers, Compose stacks, and system resources on Hetzner servers via SSH. It also includes capabilities for reloading Caddy configurations and managing Cloudflare DNS records.

A production-ready MCP server for Docker Swarm that provides full control over services, stacks, configs, and secrets with smart context preservation to reduce tool clutter.

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.

Enables comprehensive management of DuploCloud infrastructure, including tenants, services, hosts, databases, and storage. It provides tools for lifecycle operations on cloud resources like ECS tasks and S3 buckets through the Model Context Protocol.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

An MCP server that gives an AI agent controlled access to a Selectel cloud account: OpenStack cloud servers, S3 object storage, and account billing.

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

Deploys a remote MCP server on Cloudflare Workers without authentication, enabling custom tool definitions and remote connections.

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

Enables safe VPS diagnostics and Docker/Docker Compose management over SSH, providing predefined read-only and mutating tools for system monitoring, container inspection, and Compose orchestration without exposing arbitrary shell execution.

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.

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.

Enables managing Docker environments through Arcane via natural language, providing tools for containers, images, volumes, networks, and Docker Compose stacks.

A quickstart template for building and deploying secure, remote MCP servers to the cloud using Azure Functions and Node.js/TypeScript. It features integrated blob storage for snippet management and supports advanced security options like OAuth and VNET isolation.

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 building and deploying custom tool, resource, prompt, and interactive weather app endpoints on serverless infrastructure, with local debugging, built-in authentication, API Management security, and network isolation.

Enables read-only queries against a GCP PostgreSQL database, exposing tools to fetch recent users, user details by ID, and recent user activities without returning password or hash columns.

A Model Context Protocol server that exposes Firebase Firestore and Authentication to AI agents, supporting multi-project configurations and read operations.

Enables automatic weather information retrieval through a custom MCP server integrated with OpenAI using Cloudflare tunnels. Demonstrates seamless function calling between OpenAI and custom MCP tools without manual intervention.

Demonstrates how to secure an MCP server with OAuth 2.1 using AWS Cognito, with support for dynamic client registration and client ID metadata documents.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

A Model Context Protocol server deployed on Cloudflare Workers that enables interaction with PostgreSQL databases. It allows AI clients like Claude and Cursor to execute database operations via a remote SSE connection.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

Enables remote MCP connections with GitHub OAuth authentication, providing tools like add, userInfoOctokit, and image generation (restricted) deployed on Cloudflare Workers.

A Node.js-based remote Model Context Protocol (MCP) server that runs on Azure Container Apps, allowing different AI models and tools to communicate with each other in a serverless environment.

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.

A deployable Model Context Protocol server on Cloudflare Workers that allows LLMs to access custom tools without authentication requirements.

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.