MCP for AWS Cost Explorer and CloudWatch logs
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"aws-cost-explorer": {
"env": {
"AWS_REGION": "us-east-1",
"AWS_PROFILE": "YOUR_AWS_PROFILE_NAME",
"MCP_TRANSPORT": "stdio",
"BEDROCK_LOG_GROUP_NAME": "YOUR_CLOUDWATCH_BEDROCK_MODEL_INVOCATION_LOG_GROUP_NAME"
},
"args": [
"run",
"-i",
"--rm",
"-e",
"AWS_PROFILE",
"-e",
"AWS_REGION",
"-e",
"BEDROCK_LOG_GROUP_NAME",
"-e",
"MCP_TRANSPORT",
"aws-cost-explorer-mcp:latest"
],
"command": "docker"
}
}
}Are you the author?
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An MCP server for getting AWS spend data via Cost Explorer and Amazon Bedrock usage data via Model invocation logs in Amazon Cloud Watch through Anthropic's MCP (Model Control Protocol). See section on "secure" remote MCP server to see how you can run your MCP server over HTTPS.
No automated test available for this server. Check the GitHub README for setup instructions.
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An MCP server for getting AWS spend data via Cost Explorer and Amazon Bedrock usage data via Model invocation logs in Amazon Cloud Watch through Anthropic's MCP (Model Control Protocol). See section on "secure" remote MCP server to see how you can run your MCP server over HTTPS.
flowchart LR
User([User]) --> UserApp[User Application]
UserApp --> |Queries| Host[Host]
subgraph "Claude Desktop"
Host --> MCPClient[MCP Client]
end
MCPClient --> |MCP Protocol over HTTPS| MCPServer[AWS Cost Explorer MCP Server]
subgraph "AWS Services"
MCPServer --> |API Calls| CostExplorer[(AWS Cost Explorer)]
MCPServer --> |API Calls| CloudWatchLogs[(AWS CloudWatch Logs)]
end
You can run the MCP server locally and access it via the Claude Desktop or you could also run a Remote MCP server on Amazon EC2 and access it via a MCP client built into a LangGraph Agent.
This tool provides a convenient way to analyze and visualize AWS cloud spending data using Anthropic's Claude model as an interactive interface. It functions as an MCP server that exposes AWS Cost Explorer API functionality to Claude Desktop, allowing you to ask questions about your AWS spend in natural language.
Install uv:
# On macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Additional installation options are documented here
Clone this repository: (assuming this will be updated to point to aws-samples?)
git clone https://github.com/aws-samples/sample-cloud-spend-mcp-server
cd aws-cost-explorer-mcp
Set up the Python virtual environment and install dependencies:
uv venv --python 3.12 && source .venv/bin/activate && uv pip install --requirement pyproject.toml
Configure your AWS credentials:
mkdir -p ~/.aws
# Set up your credentials in ~/.aws/credentials and ~/.aws/config
If you use AWS IAM Identity Center, follow the docs to configure your short-term credentials
Uses stdio