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

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    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.
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    MIT
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    Local Cost Guard and runtime guardrails for AI agents in Claude Code.
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    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.
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    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.
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    Integrates Azure Cost Management APIs via MCP, enabling cost queries, forecasts, budgets, and Advisor recommendations through natural language in compatible clients.
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    Local-first cost tracking and model routing for MCP agents with offline token counting, budget alerts, and spend reports.
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    Enables users to analyze AWS costs, track spending trends, and detect anomalies directly within Claude Desktop using the AWS Cost Explorer API. It provides tools to identify major cost drivers and compare usage across different time periods through natural language queries.
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    Exposes rate-limit and usage data for AI coding agent CLIs as MCP tools, enabling querying of usage snapshots and reset times.
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    Reports your Claude subscription usage (5-hour and weekly limits) with a forecast and velocity recommendation, using Claude Code's existing OAuth session without requiring an API key.
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    Monitors your Cursor usage and provides a conserve flag to the agent, helping you manage request quota by batching questions, preferring defaults, and cutting unnecessary confirmations.
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    MIT
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    Exposes a get_context_usage tool that reports raw token usage from session transcripts for Claude Code and OpenAI Codex CLI, enabling agents to check context size and branch behavior.
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    An MCP server that retrieves GitHub Copilot usage metrics and seat assignment data across Enterprise, Organization, and Team levels. It allows users to monitor code completions, chat activity, and active user counts through integrated tools.
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    MIT
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    A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with your AWS environment. This allows for natural language querying and management of your AWS resources during conversations. Think of better Amazon Q alternative.
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