Browse all content tagged with Monitoring
Integrate and automate Grafana’s dashboards, datasources, and monitoring tools into AI-driven development workflows using FlowHunt's Grafana MCP Server. Enable seamless AI-powered dashboard management, query execution, and observability integration.
The Raygun MCP Server bridges AI assistants and Raygun's robust API, enabling automated error management, deployment tracking, performance monitoring, source map handling, and team management within FlowHunt workflows.
The Dynatrace MCP Server connects the Dynatrace observability platform to your AI-powered workflows in FlowHunt, enabling real-time access to production metrics, logs, anomalies, and security events for enhanced debugging, monitoring, and automation.
The Globalping MCP Server connects FlowHunt and AI assistants to a worldwide network measurement platform, enabling real-time network diagnostics, monitoring, and benchmarking directly from natural language interfaces. Run ping, traceroute, DNS, MTR, and HTTP tests from thousands of locations globally, all with robust API security and seamless integration.
The Datadog MCP Server bridges FlowHunt and Datadog’s API, enabling AI-driven access to monitoring data, dashboards, metrics, events, and logs for advanced observability and automated incident management.
The Netdata MCP Server connects AI assistants and automation tools with the Netdata monitoring platform, allowing real-time access to system metrics and streamlined observability workflows via a protocol-driven interface.
The System Health MCP Server for FlowHunt enables real-time remote Linux server monitoring—exposing CPU, memory, disk, network, and security metrics to AI assistants via the Multi-Channel Protocol. Automate infrastructure health checks, receive threshold-based alerts, and streamline DevOps workflows with direct AI integration.
The Algolia MCP Server enables FlowHunt users to connect AI assistants to Algolia’s search and analytics APIs via the Model Context Protocol, streamlining search, analytics, and monitoring workflows through natural language.
The Prometheus MCP Server enables AI assistants to interact with Prometheus metrics using standardized Model Context Protocol (MCP) interfaces. It supports PromQL queries, metric discovery, metadata access, and time-series analytics for automated monitoring and AI-driven infrastructure insights.
The Simple Loki MCP Server integrates Grafana Loki log querying into AI workflows via the Model Context Protocol. It enables AI agents to analyze, filter, and retrieve logs for observability, troubleshooting, and monitoring, using LogQL queries with flexible authentication and multiple output formats.
The VictoriaMetrics MCP Server bridges AI assistants with the VictoriaMetrics time series database, enabling seamless querying, management, and integration of time series metrics into AI-driven workflows and applications.
Explore the importance of logging in AI workflows, how FlowHunt enables detailed logs for tool calls and tasks, and best practices for monitoring, debugging, and optimizing AI systems.
