A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.
A secure, containerized MCP server that enables AI assistants to manage Terraform infrastructure using integrated Language Server Protocol (LSP) tools. It facilitates safe operations like initialization, validation, and planning while providing context-aware code completion and documentation.
Connects AI models to the Terraform Registry via MCP, enabling provider lookups, resource usage examples, and module recommendations for streamlined Terraform workflows.
Enables AI clients to perform local code search, indexing, and analysis across Java, JavaScript/TypeScript, .NET/C#, and Python projects through the MCP protocol.
MCP server that analyzes codebases to provide dependency graphs, impact analysis, and file insights across 15+ programming languages, enabling AI assistants to understand project structure and navigate code efficiently.
