"Using Terraform to Provision AWS Resources and Ansible to Configure Services" matching MCP servers:

Enables Claude Desktop to trigger Ansible-driven log scans across an inventory group and retrieve combined results from target hosts.

Enables Claude Desktop to interact with 57 AWS services using over 200 tools and local machine profiles. It supports multi-profile configurations and features a read-only safe mode by default to manage infrastructure like EC2, S3, and Lambda securely.

MCP server that exposes Avangenio's service status by fetching and parsing status.avangenio.com/data.txt into normalized JSON.

A read-only Model Context Protocol server that exposes over 60 AWS tools across services like EC2, S3, and IAM for AI agent interaction. It features multi-region support, resource caching, and audit logging to provide secure, AI-ready access to AWS infrastructure data.

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 assistants to troubleshoot AWS and hybrid network connectivity by analyzing hop-by-hop paths across security groups, NACLs, route tables, Transit Gateway routes, VPN/BGP, DNS, and flow logs to identify blocking rules and suggest fixes.

A read-only MCP server for safe, structured investigation of AWS serverless resources, providing curated tools for tracing dependencies, permissions, and failures without exposing raw SDK access.

Enables LLM clients to query AWS CloudWatch Logs and Alarms through MCP tools.

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.

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

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.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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 precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables infrastructure operations including provisioning, configuration, monitoring, compliance auditing, and auto-remediation through natural language, using Terraform and Ansible tools exposed over MCP.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

Cross-cloud observability for AI agents. Discover resources, correlate logs, and diagnose infrastructure issues across AWS, GCP, Vercel, and Cloudflare — without leaving your editor.

MCP server for Exit1 uptime monitoring. Enables AI assistants to create and manage uptime checks, configure alerts, and query status via natural language.

Enables AI assistants to monitor, analyze, and configure OWASP ModSecurity CRS via Docker, with tools for overview, drill-down, and rule/IP management.

Enables interaction with the Mackerel monitoring platform, providing tools to manage alerts, hosts, dashboards, services, monitors, and traces.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

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

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.

A professional-grade MCP server that enables AI assistants to monitor web services, APIs, and HTTP endpoints with enterprise-level security.

Provides read-only access to multiple production services with unified status and timeline tools for cross-service monitoring and diagnostics.