"Using Terraform to Provision AWS Resources and Ansible to Configure Services" matching MCP servers:

Enables AI agents to provision and manage external SaaS services (Clerk, Stripe, Resend, etc.) by authenticating and creating resources via YAML configuration.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Cloud infrastructure provisioning via natural language. Enables deploying production-ready infrastructure on AWS, GCP, Azure, or Oracle with a single prompt.

Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

Read-only server that reports what is actually true in a local Ansible checkout: the option specs of installed modules, task-argument validity checks, role interfaces, redacted inventory, play structure, effective config, requirements drift, and which tasks a collection upgrade would break. It lets coding agents verify specs and arguments against the installed collections before writing anything, without running plays, connecting to managed hosts, or supplying vault secrets.

This MCP server enables Claude to speak summaries, announcements, and explanations aloud using text-to-speech — right from your terminal.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

Enables managing Ansible playbooks, inventories, and execution through MCP.

A Model Context Protocol server that converts Markdown content to HTML format.

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

Turns any OpenAPI REST or GraphQL API into an MCP server, allowing AI assistants like Claude to interact with APIs without writing code.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Enables existing Express routers to be exposed as MCP tools, dispatching tool calls through the Express middleware stack in-process without a network hop.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

Enables users to record, review, verify, and expose permitted browser workflows as callable MCP tools with typed inputs, isolated Chromium verification, and approval-gated writes.

Enables AI agents to convert GitHub Flavored Markdown into formatted Word (.docx) files, including headings, lists, tables, links, code and images, with an optional Chinese official document (公文) font preset. Conversion runs locally, so no content is uploaded.

Enables AI agents to convert CSV text into JSON arrays with automatic delimiter detection and optional header-row handling, accessed through a pay-per-call x402 micropayment API.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

Enables agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

Enables MCP clients to expose selected operations from local OpenAPI 3.0/3.1 documents as tools, with stdio serving or generated standalone server projects and read-only defaults.