@MCP-Mirror
基本情報
Mirror of
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This MCP server retrieves AWS spend data via Cost Explorer and Amazon Bedrock usage data from CloudWatch Model invocation logs. It integrates with Anthropic’s Model Context Protocol (MCP) so users can analyze cloud costs and Bedrock usage through natural language conversations with Claude.
Install uv, clone the repository, create a Python 3.12 virtual environment, and install dependencies. Set your AWS credentials, export MCP_TRANSPORT (use stdio for local or sse for remote) and BEDROCK_LOG_GROUP_NAME, then run python server.py. Configure Claude Desktop by adding a Docker or UV entry to claude_desktop_config.json. For a remote server, deploy on EC2 with MCP_TRANSPORT=sse and test using mcp_sse_client.py.
Python 3.12, AWS credentials with read-only access to Cost Explorer and CloudWatch, and Anthropic API access for Claude integration. Optionally, Bedrock access for the LangGraph agent and EC2 for a remote server.
Add either a Docker entry (using the `aws-cost-explorer-mcp:latest` image) or a UV entry pointing to your local repository in the `mcpServers` section of `claude_desktop_config.json`. Include your AWS credentials and Bedrock log group name as environment variables.
Four tools: `get_ec2_spend_last_day()`, `get_detailed_breakdown_by_day(days)`, `get_bedrock_daily_usage_stats(days, region, log_group_name)`, and `get_bedrock_hourly_usage_stats(days, region, log_group_name)`.
Yes. Set `MCP_TRANSPORT=sse` to run the server on EC2. Claude Desktop does not currently support remote MCP servers, but you can test with the provided `mcp_sse_client.py` or use the Chainlit app with a LangGraph agent.
No. MCP uses JSON-RPC 2.0 without built-in authentication or authorization. Avoid sending sensitive data. For secure remote access, the README describes an optional nginx reverse proxy with HTTPS using an SSL certificate.
MCP server connecting to Kubernetes
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