"AWS Cost and Usage Analysis with Cost Optimization Recommendations" matching MCP servers:

Plan AWS disaster recovery budgets conversationally, comparing backup/restore, pilot light, warm standby, and active/active strategies using live Cost Explorer data.

Tracks AI agent token usage and spending in real time, with budget alerts, per-task cost breakdown, and a visual dashboard.

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.

An MCP server for unified cost tracking and analysis across AWS, OpenAI, and Anthropic. It enables users to query expenditures, compare costs across providers, and analyze usage trends through natural language.

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.

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

Estimates Claude API token counts, per-model cost, and prompt-caching break-even without an API key or network.

Integrates Azure Cost Management APIs via MCP, enabling cost queries, forecasts, budgets, and Advisor recommendations through natural language in compatible clients.

A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.

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.

An MCP server that gives Claude live access to Azure pricing and cost data — retail prices, VM comparisons, reservation analysis, architecture estimates, and actual subscription spend.

Provides aggregated municipal development costs for US jurisdictions, including impact fees and utility connection charges, enabling AI agents to assess building feasibility quickly.

Provides cost analysis of AI agent usage by previewing scrubbed metadata before upload and analyzing spend, cache-hit rates, and waste recovery through a local or remote server.

Token-cost telemetry for OpenClaw, queryable from Claude or any MCP-aware agent. Provides per-agent and per-provider cost attribution, anomaly detection, model-routing recommendations, and 30-day forecasts.

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.

Read-only MCP server for the Renology 2026 city-level renovation cost dataset. Enables AI assistants to list markets and project types, retrieve cost ranges, compare costs across cities, and access methodology and citation information.

Enables analyzing AWS cloud spending and Bedrock usage through natural language queries using Claude.

Enables AI agents to discover long-tail podcasts through randomized probe queries, trend lookups, and RSS feed peeks, providing cadence, episode length, and feed details without requiring API keys.

Enables AI agents to get book recommendations by topic or mood, discover serendipitous blind-date picks from first sentences, and access free public-domain classics with read-now availability, all with no API keys required.

MCP server for querying OpenAI usage and cost data, including spend summaries, daily breakdowns, month-over-month comparisons, and token usage by model.