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

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

Enables sending web push notifications and managing Pushpad resources (notifications, subscriptions, projects, and senders) through natural language, using the Pushpad API.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

Provides access to Deutsche Bahn train timetables, station information, and schedule changes through Model Context Protocol tools and resources.

A Model Context Protocol server that enables AI assistants to interact with MongoDB Atlas resources through natural language, supporting database operations and Atlas management functions.

A Model Context Protocol server that provides persistent storage, categorization, and retrieval of bookmarks through AI clients like Claude. It allows users to manage web links using custom categories and includes options for local JSON storage or AWS S3 synchronization.

Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.

A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.

A Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.

MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resources for client-side exploration.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.