EBS CloudWatch Metrics
Provides tools to query and calculate AWS EBS performance metrics from CloudWatch, including IOPS, throughput, and latency. It also enables users to manage snapshots and retrieve advanced diagnostic data like I/O utilization and burst balance.
What is EBS CloudWatch Metrics?
EBS CloudWatch Metrics is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to provides tools to query and calculate aws ebs performance metrics from cloudwatch, including iops, throughput, and latency. it also enables users to manage snapshots and retrieve advanced diagnostic d...
Provides tools to query and calculate AWS EBS performance metrics from CloudWatch, including IOPS, throughput, and latency. It also enables users to manage snapshots and retrieve advanced diagnostic data like I/O utilization and burst balance.
This server falls under the Monitoring & Observability category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Provides tools to query and calculate AWS EBS performance me
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx ebs-cloudwatch-metrics-mcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about EBS CloudWatch Metrics
What is EBS CloudWatch Metrics?
EBS CloudWatch Metrics is a Model Context Protocol (MCP) server that provides tools to query and calculate aws ebs performance metrics from cloudwatch, including iops, throughput, and latency. it also enables users to manage snapshots and retrieve advanced diagnostic data like i/o utilization and burst balance. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install EBS CloudWatch Metrics?
Follow the installation instructions on the EBS CloudWatch Metrics GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with EBS CloudWatch Metrics?
EBS CloudWatch Metrics works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is EBS CloudWatch Metrics free to use?
Yes, EBS CloudWatch Metrics is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
EBS CloudWatch Metrics Alternatives — Similar Monitoring & Observability Servers
Looking for alternatives to EBS CloudWatch Metrics? Here are other popular monitoring & observability servers you can use with Claude, Cursor, and VS Code.
Netdata
★ 78.9kReal-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Kubeshark
★ 11.9keBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.
Mission Control
★ 4.9kSelf-hosted AI agent orchestration platform: dispatch tasks, run multi-agent workflows, monitor spend, and govern operations from one mission control dashboard.
Grafana
★ 3.0kThis MCP server enables natural-language querying of Grafana logs by automatically detecting log sources and service labels. It provides read-only access to log data with intelligent caching for efficient repeat queries.
Sentrux
★ 2.4kReal-time architectural sensor that helps AI agents close the feedback loop, enabling recursive self-improvement of code quality. Pure Rust.
OpenInference
★ 986OpenTelemetry Instrumentation for AI Observability
Browse More Monitoring & Observability MCP Servers
Explore all monitoring & observability servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up EBS CloudWatch Metrics in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use EBS CloudWatch Metrics?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.