#gcp

AI-powered knowledge base for your Terraform modules. Index, search, compose, and audit - all from one place.

B2AI infrastructure API for autonomous agents. Normalizes AWS, Azure, and GCP into a unified schema. Returns execution kits (Terraform + CLI), cost estimates, and cross-provider recommendations. Built for AI agents that need to discover, evaluate, and deploy cloud infrastructure programmatically.

Kubernetes cluster cost analysis and optimization. Query costs, find savings opportunities, get rightsizing recommendations, and analyze pod spend across AKS, EKS, and GKE directly from Claude.

Conversational AI agent that designs AWS/GCP architecture, generates Terraform, estimates costs, and deploys — all through MCP.

Cross-cloud observability for AI agents. Discover resources, correlate logs, and diagnose infrastructure issues across AWS, GCP, Vercel, and Cloudflare — without leaving your editor.

CloudForge MCP lets Claude visualise your cloud architecture diagrams, generate production-ready Terraform HCL from natural language, import existing IaC, and manage Azure, AWS, and GCP resources — all from chat. Authenticate with a CloudForge API key (cf_live_...) generated from cloudforge.cloud/account. No browser token copying required. Tools included: • cloudforge_diagram_to_mermaid — render any saved diagram inline in Claude • cloudforge_architecture_summary — resource counts, central components, inline diagram • cloudforge_generate_terraform — generate .tf files from a description • cloudforge_export_terraform_from_diagram — export Terraform from a saved diagram • cloudforge_import_terraform — parse existing HCL → diagram + Mermaid preview • cloudforge_chat — ask the AI Architect for cost, security, and best practice advice • cloudforge_suggest_resources — get AI-recommended resources for a use case • cloudforge_list_diagrams / get / save / delete / recent — full diagram management • cloudforge_list_members / invite / remove — organisation management

The Defang Model Context Protocol (MCP)⁠ Server is tailored for developers who work primarily within integrated development environments (IDEs). It enables seamless cloud deployment from supported editors such as Cursor, Windsurf, VS Code, VS Code Insiders, and Claude, delivering a fully integrated experience without leaving your development environment.

A MCP server implementation for Google Cloud using Go and Cobra.

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with your Google Cloud Platform environment. This allows for natural language querying and management of your GCP resources during conversations.

🤖 A Model Context Protocol (MCP) server for Google Cloud