What does AWS Bedrock Logs MCP require to run?
Python 3.13+, AWS credentials with CloudWatch Logs access, and Anthropic API access for Claude integration.
@dheerajoruganty
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"aws_bedrock_logs": {
"command": "uv",
"args": [
"--directory",
"/path/to/aws-bedrock-logs-mcp",
"run",
"cloudwatch_mcp_server.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A command-line interface and API for analyzing AWS Bedrock usage and logs through Anthropic's MCP (Model Control Protocol). It exposes AWS CloudWatch Logs API functionality to Claude, allowing you to query and analyze Bedrock usage data in natural language.
Install via uv, configure AWS credentials, then start the server with python cloudwatch_mcp_server.py. For Claude Desktop, add the server configuration to your mcpServers JSON block with the uv command. Four tools are exposed: get_bedrock_logs_df, get_model_usage_stats, get_user_usage_stats, and get_daily_usage_stats.
Python 3.13+, AWS credentials with CloudWatch Logs access, and Anthropic API access for Claude integration.
By default, the server uses stdio transport for communication with MCP clients.
It retrieves raw Bedrock invocation logs and aggregated statistics from AWS CloudWatch Logs via the CloudWatch Logs API. No Bedrock data is stored locally—it is queried on demand.
boto3, mcp[cli] (Anthropic’s Model Control Protocol library), pandas, and pydantic.
Yes, a Dockerfile is included in the repository for container deployments.

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