"Google Home" matching MCP servers:

Lets AI agents draw professional cloud architecture diagrams with the official AWS, Azure and Google Cloud icons, from a plain description, a JSON graph or Terraform code.

Exposes the Polaris architectural fitness-function control plane's REST API as grouped MCP tools over stdio, letting agents manage tribes, squads, fitness targets and functions, measurement sources, submissions, evaluations, waivers, insights, and events. Handles Google OIDC login and silent token refresh automatically, and submits measurements with an ingest API key.

An automated MCP server for Google Stitch that enables AI-driven UI design generation, accessibility audits, and design system management. It streamlines workflows for creating responsive screens, extracting design tokens, and maintaining visual consistency across professional web projects.

An automated MCP server for Google Stitch that enables AI-driven UI design generation, screen management, and design system extraction. It provides 19 professional tools for creating consistent web interfaces, conducting accessibility audits, and exporting design tokens.

A local-first MCP server for manually building, inspecting, and saving directed acyclic graphs (DAGs) for custom days, with optional evidence summaries from Home Assistant.

Exposes 20+ tools that let any MCP-compatible client search patent rules and statutes (MPEP, USC, CFR) with hybrid RAG retrieval, hunt prior art across 100M+ patents via Google BigQuery, run automated claims and application compliance checks, and generate patent-style diagrams. It also provides CLI-driven setup, GPU-accelerated indexing, and health reporting so users can move from a raw invention description to a reviewable draft application.

CodeGraph MCP is a powerful standalone tool that parses your entire C/C++ codebase into a semantic knowledge graph and seamlessly exposes it to AI coding assistants via the Model Context Protocol (MCP). By providing AI (like Claude Desktop, Cursor, or Google Antigravity) with a structural map of your project—including caller/callee relationships, file dependencies, and dynamic function definition

Enables modular MCP capabilities by organizing tools, resources, and prompts into composable sub-servers, exposed either all-in-one or as separate MCP endpoints.