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aws-pricing-mcp

by trilogy-group
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Python
MIT License
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AWS EC2 定价 MCP 服务器

AWS EC2 定价 MCP 服务器允许任何 LLM 或自动化脚本通过一次调用查询实时 EC2 定价。它由预先解析的 AWS 定价目录提供支持，可以回答以下问题：

What is the cheapest EC2 instance with 32GB RAM?

Which AMD instances have more than 3.5 Ghz CPUs?

What is the 3-yr All Upfront discount on r6g family in eu-west-1?

What is the cheapest instance to run Windows with SQL Server Enterprise?

使用 Docker

使用 Docker hub 镜像

将此 mcp_config.json 用于 Docker hub 镜像：

{ "mcpServers": { "AWS EC2 Pricing MCP": { "command": "docker", "args": ["run", "--rm", "-i", "-q", "--network", "none", "ai1st/aws-pricing-mcp"] } } }
  • --rm标志在容器退出时删除该容器。
  • -i标志启用 stdio 通信的交互模式。
  • -q标志抑制有关下载图像的 docker 消息。
  • --network none完全断开容器与网络的连接，以保证不会泄露数据。

使用本地图像

构建图像：

docker build -t aws-pricing-mcp . --build-arg BUILD_DATE=$(date +%Y-%m-%d)

这将下载价格数据并构建镜像。BUILD_DATE 参数确保在构建期间下载最新的价格数据。

本地构建图像的示例 mcp_config.json：

{ "mcpServers": { "AWS EC2 Pricing MCP": { "command": "docker", "args": ["run", "--rm", "-i", "--network", "none", "aws-pricing-mcp"] } } }
  • --rm标志在容器退出时删除该容器。
  • -i标志启用 stdio 通信的交互模式。
  • --network none完全断开容器与网络的连接，以保证不会泄露数据。

直接使用 Python

您需要先下载定价数据：

curl https://cloudfix-public-aws-pricing.s3.us-east-1.amazonaws.com/pricing/ec2_pricing.json.gz | gunzip > ec2_pricing.json

它应该与 server.py 位于同一目录中。

本地 Python 的示例 mcp_config.json：

{ "mcpServers": { "AWS EC2 Pricing MCP": { "command": "python", "args": [ "/path/to/server.py" ] } } }

搭建说明

有关构建和发布 Docker 镜像的说明，请参阅BUILD.md 。

定价数据 JSON 格式

请参阅PRICING.md 。

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

AWS EC2 定价 MCP 服务器允许任何 LLM 或自动化脚本通过一次调用查询实时 EC2 定价。它由预先解析的 AWS 定价目录提供支持，可以回答以下问题：

具有 32GB RAM 的最便宜的 EC2 实例是什么？

哪些 AMD 实例具有超过 3.5 Ghz 的 CPU？

eu-west-1 地区 r6g 系列 3 年全额预付折扣是多少？

运行带有 SQL Server Enterprise 的 Windows 的最便宜实例是什么？

  1. 使用 Docker
    1. 使用 Docker hub 镜像
    2. 使用本地图像
  2. 直接使用 Python
    1. 搭建说明
      1. 定价数据 JSON 格式

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