"Using Linear with team-specific templates for ticket creation" matching MCP servers:

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.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

Shows your current Claude Desktop activity as Discord Rich Presence, including model, status, usage, and subscription info.

Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.

Brings live project context into Slack via MCP, enabling developer teams to check service health, recall team decisions, search code, and query project context directly from chat.

Enables real-time communication and orchestration of multiple AI agents with a web dashboard for monitoring agent activities, tasks, and artifacts.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Provides tools for obtaining system CPU and memory statistics through FastAPI endpoints exposed via MCP.

A read-only Model Context Protocol server that enables interaction with Unimus network configuration management system directly via LLMs, providing access to device data, backups, and configuration analysis.

A trademark research and monitoring MCP server that provides access to a normalized trademark corpus across 30+ registers, with provenance on every record, watch/monitoring capabilities, conflict research via Nice class, and portfolio management tools—without returning legal verdicts, leaving availability judgments to qualified professionals.

A remote MCP server that provides AI agents access to the Rootly API for incident management, allowing users to query and manage incidents, alerts, teams, services, and other incident management resources through natural language.

Provides detailed Lighthouse audits for web pages, returning specific failing elements with actionable suggestions and HTML snippets.

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

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.