"Amazon CloudWatch" matching MCP servers:

Enables searching and analyzing AWS CloudWatch logs with support for configurable log groups, time-based searches, and service-specific log stream filtering.

Enables AI agents to query AWS CloudWatch metrics, alarms, and logs read-only via MCP, providing rapid health snapshots and triage without console navigation.

Enables LLMs to autonomously query AWS CloudWatch Logs and perform structured root-cause analysis via natural language prompts, using MCP tools for log group listing and Insights queries.

Enables an AI assistant to read and query Amazon CloudWatch metrics, logs, and alarms through read-only MCP tools.

Enables natural language queries for AWS CloudWatch logs, metrics, and alarms via an LLM agent with MCP tools.

Provides AI assistants with read-only access to AWS CloudWatch Logs for production debugging and log analysis, enabling error searching and bug report generation.

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.

Manage AWS, Hetzner, OVH, and custom SSH servers from AI agents — commands, logs, CloudWatch/CloudTrail, IP banning, and S3, with guard tiers and a full audit trail.

A read-only MCP server that lets an AI assistant inspect a single AWS lab instance's EC2 health, recent system/nginx errors from CloudWatch, and nginx service status via SSM, with strict allowlisting and no generic shell access.

MCP server for analyzing OpenTelemetry traces with performance and error diagnosis, supporting loading from files, AWS X-Ray, and CloudWatch.

A debugging gateway for distributed systems that provides 17 tools for interacting with AWS CloudWatch, Step Functions, LangSmith, and Jira. It enables efficient log analysis, workflow tracing, and ticket management while significantly reducing token usage through a single-interface discovery pattern.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

An MCP server that connects Claude (or any MCP compatible client) to your existing log infrastructure. Query, summarize, and trace logs in plain English across GCP Cloud Logging, AWS CloudWatch, Azure Log Analytics, Grafana Loki, and Elasticsearch without writing filter expressions or leaving your editor.

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

Monitor and analyze AWS ECS services, including service status, CloudWatch metrics, and load balancer integration.

A read-only MCP server that exposes tools to query Datadog monitors and logs, and AWS CloudWatch Logs, and to group recurring errors by fingerprint. Designed for use with Claude Code to diagnose issues and propose fixes.

Enables AI agents to diagnose and analyze AWS serverless infrastructure through Model Context Protocol, providing access to CloudWatch logs, Lambda functions, DynamoDB tables, IAM policies, and Bedrock-powered incident root-cause analysis.

Enables secure tool discovery and execution on AWS Lambda with role-based access control, command injection defense, and sensitive data redaction, allowing managed CloudWatch log queries and Terraform operations through a standard MCP interface.

An MCP server on AWS Lambda that gives AI assistants read-only access to SQS dead-letter queues and CloudWatch logs for fast incident triage.

MCP server for AWS infrastructure analysis. Connects to DynamoDB, Lambda, SQS, SNS, Secrets Manager, EventBridge, RDS, PostgreSQL, MongoDB, and CloudWatch — surfaces missing indexes, queue DLQs, Lambda config issues, IaC drift, and security findings for Claude Code and Cursor.