"Creating a Weather Forecast System" matching MCP servers:

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

MCP server and CLI for AlmaLinux Build System (ALBS) that enables AI coding assistants to investigate build failures, create builds, sign packages, and manage release plans through natural language.

Provides AI assistants direct access to Apple's App Store Connect API, enabling them to manage apps, provisioning data, TestFlight builds, and App Store versions, including creating versions, attaching builds, and submitting for review.

A local MCP server that exposes Bazel build system capabilities to AI assistants.

MCP server for Beaker lab automation, enabling system provisioning, job management, distro discovery, and failure diagnosis through 25 tools.

Enables Claude to interact with Infracost for Terraform cost estimation and cloud governance. Supports generating cost breakdowns, comparing configurations, creating tagging policies, setting up cost guardrails, and posting cost comments to PRs.

LoopSense is an open-source MCP server that closes the feedback loop for AI coding agents — giving them real-time visibility into CI results, deployments, test outcomes, and file system changes.

MCP server for managing Netlify sites, enabling operations such as creating sites from GitHub repositories, listing, viewing details, and deleting sites.

A local MCP server that exposes Bazel build system functionality to AI agents, allowing them to build, test, query, and manage Bazel projects through natural language even in environments where Bazel can't be directly accessed.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

Enables AI assistants to interact with Coolify self-hosted instances for application deployment, management, and monitoring. Features 4 unified tools optimized for VS Code's limits, covering app management, environment configuration, system administration, and built-in documentation.

Enables AI assistants to interact with Netflix Conductor Workflow Engine for troubleshooting workflows, managing executions, and creating/updating workflow and task definitions through natural language.

Enables AI assistants to manage Rundeck operations including jobs, executions, projects, nodes, system management, key storage, webhooks, and ACL policies via natural language.

Enables comprehensive Jenkins automation through MCP interface, allowing users to manage builds, jobs, artifacts, and queues with natural language commands. Supports build triggering, monitoring, artifact retrieval, and system status checks with automatic CSRF protection and authentication.

Enables comprehensive test management in Zephyr Scale Cloud, including creating and managing test cases, executing tests with step-by-step results, organizing test cycles and plans, and performing advanced JQL searches.