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

A Model Context Protocol (MCP) server that integrates Claude with the Terraform Cloud API, allowing Claude to manage your Terraform infrastructure through natural conversation.

Enables Terraform HCL plan generation, drift detection, and strict human confirmation approval barriers for cloud infrastructure management.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

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 hybrid (BM25 + vector) search over Terraform AWS and Google provider documentation, with tools for ranked search and full document retrieval.

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

Enables AI agents to interact with a Git-native organizational governance system, supporting proposal-validation workflows, decision-making, and audit trail management through 21 MCP tools over stdio transport.

An advisory and generative copilot for Terraform that reviews existing scripts and generates compliant infrastructure using organization-specific rules.

Enables AI agents to manage Terraform modules by searching, inspecting, and scaffolding configurations from private GitHub repositories. Also provides backend S3 configuration for generated Terraform code.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

Enables generating, validating, planning, and applying Terraform configurations to manage infrastructure through natural language.

A FastMCP-based server that provides a natural language interface to Terraform operations, enabling infrastructure management via simple English commands.

Generates structured prompts for Claude Code to create comprehensive Terraform test cases including unit, integration, and mock tests.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

A containerized Model Context Protocol server that enables using natural language to develop AWS infrastructure with Terraform, offering best practices guidance, security scanning with Checkov, and access to AWS provider documentation.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

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.

Exposes eight MCP tools over streamable HTTP that let clients ingest alerts, list and diagnose incidents, analyze Terraform plan risk, propose remediations, and dry-run or execute policy-validated, approval-gated changes with automatic rollback.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Enables AI coding assistants to run static analysis on GitHub repositories, raw code snippets, or local directories to detect cloud cost leaks in Terraform/AWS configs, PostgreSQL migration table-lock hazards, and OWASP/Next.js API security gaps. Each finding returns structured severity, line-level detail, and drop-in fixes.

Enables AI agents to manage virtualization, Active Directory, Windows hosts via WinRM, PostgreSQL databases, and shell/SSH environments through Model Context Protocol tools.

Provides tools to execute Terraform commands, analyze plan outputs for resource changes, and generate detailed markdown reports. It supports custom environment variables and filtering patterns to streamline infrastructure analysis and management.

Exposes multiple LLM providers (AWS Bedrock, OpenAI, Google Gemini, local Ollama) as MCP tools with automatic routing by task type and Prometheus metrics, enabling any MCP-compatible client to generate text, route prompts, and list providers.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

A read-only MCP server that analyzes a supplied Terraform plan JSON file and returns resource identities, action/type/mode counts, and coverage warnings about proposed infrastructure changes. It never executes Terraform, applies changes, or connects to AWS, keeping analysis local and deterministic.

Open-source AWS security scanner with Attack Chains, Breach Cost Estimation, and MCP Server. 47 checks across 15 AWS services. Every finding includes copy-paste remediation (CLI + Terraform) and a dollar-risk estimate with verified source. First free standalone AWS security MCP server - Prowler and Wiz require paid SaaS.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.