Prometheus is an open-source systems monitoring and alerting toolkit. It collects and stores metrics as time series data, with flexible queries and real-time alerting.
Why this server?
Enables monitoring of the MCP server using Prometheus-compatible clients.
Why this server?
Provides integration with Prometheus for metrics collection and monitoring as part of the Coroot observability stack.
Why this server?
Planned future support for exporting metrics to Prometheus as part of enterprise features
Why this server?
Exposes metrics endpoints for monitoring server performance and usage statistics
Why this server?
Generates monitoring setups with Prometheus for metrics collection and alerting
Why this server?
Enables natural language querying and analysis of Prometheus metrics, with tools for metric discovery, label exploration, target inspection, and executing both instant and range queries against a Prometheus monitoring server.
Why this server?
Provides access to Prometheus metrics and queries, allowing execution of PromQL queries, metrics discovery and exploration, viewing instant and range query results, and retrieving target information from a Prometheus server.
Why this server?
Includes monitoring capabilities through Prometheus integration, allowing performance tracking and metrics collection
Why this server?
Enables querying and managing Prometheus Alertmanager resources including status, alerts, silences, receivers, and alert groups. Supports creating new alerts, managing silences (create, update, delete), and retrieving alert information through the Alertmanager API v2.
Why this server?
Provides tools for monitoring and metrics collection through Prometheus, allowing for querying and visualization of time-series data.
Why this server?
Allows querying Prometheus data sources, retrieving metric metadata, listing metric names, and exploring label names and values to analyze time series data.
Why this server?
Enables importing Prometheus exposition format data and executing PromQL queries against the VictoriaMetrics database.
Why this server?
Supports querying and analyzing Prometheus metrics through Grafana, enabling AI-powered interpretation of time-series data for system performance monitoring and anomaly detection.
Why this server?
Supports Prometheus-compatible functionality including querying with PromQL, metric relabeling rules debugging, and integration with Prometheus configuration when used as a scraper for VictoriaMetrics.
Why this server?
Integrated for monitoring system performance and metrics collection in production deployments.
Why this server?
Enables executing PromQL queries against Prometheus datasources configured in Grafana, optimizing time series responses to reduce token size.
Why this server?
Incorporates Prometheus for metrics collection and monitoring as part of the production deployment stack
Why this server?
Provides real-time server metrics through a dedicated port, enabling monitoring of server performance statistics like TPS, memory usage, online players, and loaded chunks.
Why this server?
Exposes metrics for monitoring server performance and operations through a dedicated metrics endpoint compatible with Prometheus.
Why this server?
Exposes metrics in Prometheus format at the /metrics endpoint for monitoring and observability in production environments.
Why this server?
Collects and exposes metrics for monitoring server performance and usage patterns
Why this server?
Includes metrics collection for monitoring request counts, response times, and error rates through a dedicated /metrics endpoint.
Why this server?
Exposes metrics endpoints for monitoring service performance, analysis success rates, and data completeness scores.
Why this server?
Suggested for monitoring the MCP server in production environments
Why this server?
Enables querying and monitoring metrics through Prometheus, including instant queries, range queries, alerts, and targets
Why this server?
Enables data retrieval and analysis from Prometheus databases, including fetching specific metrics, performing statistical analysis, searching metric usage patterns, and executing complex PromQL queries for in-depth data exploration.
Why this server?
Collects metrics from AI model operations, enabling detailed monitoring of performance, usage patterns, and resource utilization.
Why this server?
Allows to interact with Prometheus metrics and data, including listing and accessing metric schema, metadata, and statistical information (count, min, max values)
Why this server?
Provides metrics for monitoring server performance, including RPC requests, latency, rate limiting, and active connections, accessible at the /metrics endpoint.
Why this server?
Exposes Prometheus metrics via a /metrics endpoint for monitoring server performance
Why this server?
Optional integration for metrics collection and alerting
Why this server?
Supports system monitoring via Prometheus
Why this server?
Allows access to Prometheus monitoring data through an MCP server, supporting authentication via username/password or token, and compatibility with multi-tenant setups through organization ID specification.
Why this server?
Enables access to Prometheus monitoring and time-series data through an MCP server, allowing AI assistants to query metrics, analyze performance data, and interact with Prometheus instances.
Why this server?
Enables comprehensive monitoring and metrics collection for the Sequential Questioning server
Why this server?
Collects and stores monitoring metrics for the MCP server deployment