"A platform for managing infrastructure as code with Terraform Cloud" matching MCP servers:

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Enables AI assistants to interact with Terraform Cloud workspaces and runs, including checking run status, listing workspaces, and retrieving detailed information about workspaces and runs.

The Terraform MCP Server is a Model Context Protocol (MCP) server that integrates seamlessly with Terraform Registry and HCP Terraform APIs, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.

MCP server for managing Terraform infrastructure as code, enabling initialization, planning, applying, destroying, validating, and showing state of Terraform configurations.

Exposes Terraform/Terragrunt tooling as Claude Code tools for generating variables.tf and mock outputs automatically from input files.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Delegates expensive or long-running AI tasks to Kubernetes-hosted Claude agents running on OpenShift. Enables creating, managing, and monitoring remote agentic sessions for complex work like codebase analysis and security audits.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

Turns Claude-style skill folders into MCP tools, resources, and prompts for discovering and using skills.

Provides AI agents with natural language control over AWS, Azure, GCP, and Alibaba Cloud infrastructure through dynamic API discovery and execution. Supports 51,900+ cloud operations and includes OpenTofu integration for complete infrastructure lifecycle management.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables deployment and management of GPU workloads across multiple cloud providers (RunPod, Vast.ai) with intelligent GPU selection, resource monitoring, and telemetry tracking through Redis, ClickHouse, and SkyPilot integration.

MCP server for the Partiri Cloud PaaS platform. Enables AI agents to manage workspaces, projects, services, deployments, and metrics.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

A read-only MCP server for Akamai Cloud (Linode) that lets users ask plain-language questions about their account, including inventory, pricing, GPU availability, and account limits.

Dynamic QR code platform for AI agents. Create, customize, and track QR codes without regenerating images. 37 tools covering 11 QR types (URL, vCard, WiFi, event…).

Enables AI agents to manage infrastructure by exposing Terraform tasks and deployments as tools via STDIO or SSE.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables MCP-compatible AI agents to deploy and manage applications on Google Cloud Run, including service deployment, listing, logging, and project creation.