"Terraform Cloud - Managing Cost and Performance" 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.

A read-only MCP server for inspecting and diagnosing HCP Terraform workspaces, runs, and plan summaries from ChatGPT and other MCP clients. It provides tools to list workspaces, inspect runs, and summarize plans without exposing sensitive data.

Multi-cloud pricing comparison MCP server that enables natural language queries to compare compute, storage, egress, and Kubernetes costs across AWS, Azure, GCP, and OCI.

Provides read-only visibility into Snowflake warehouse cost and query performance, including credit usage by warehouse, expensive queries, and heuristic right-sizing recommendations.

An MCP server that enables querying performance review periods, records, details, and saving self-assessment drafts without final submission.

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

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

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

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.

AutomateLab SEO Performance combines search and analytics data into clear actions for each URL. Find content to refresh and track results from your MCP client. Product and documentation: https://automatelab.tech/products/mcp/seo-performance-mcp/

Enables interactive recipe costing and menu-item pricing with deterministic math, including waste and margin calculations, and distinguishes whether figures came from the calculator or the model.

Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.

Enables comprehensive analysis of AWS Lambda performance including cold start tracking, memory utilization monitoring, cost analysis, and optimization recommendations. Provides real-time metrics, comparative analysis across multiple functions, and actionable insights to improve Lambda performance and reduce costs.

Connects AI models to the Terraform Registry via MCP, enabling provider lookups, resource usage examples, and module recommendations for streamlined Terraform workflows.

Generates formatted performance review documents by providing employee details, review period, accomplishments, and improvement areas.

Enables querying AWS Cost and Usage Report data via Amazon Athena for cost-effective and detailed cost analysis.

Token cost math for LLM API calls: current per-million-token rates for 69 models across 17 providers, with local arithmetic for estimates, comparisons and monthly budgets. Rates are verified and date-stamped.

A Python-based MCP server that analyzes PostgreSQL query plans, suggests indexes, and checks pagination safety to help optimize database performance.

Per-unit cost of 13 back-office tasks done by a person vs by software, in the US, Greece and Ukraine, with an official statistic behind every hourly wage. Bundled data, works offline.

Lets AI agents estimate the cost and result size of BigQuery and Snowflake queries before they run, then execute them only within per-call byte, row, and dollar bounds. Estimates are labeled with an accuracy tier so agents never over-trust an approximate figure.