Provides tools for DeepTempo AI SOC including findings and case management, investigation workflow orchestration, action approval workflows, and MITRE ATT&CK layer generation.
An MCP server that enables interaction with Google Cloud Logging API, allowing users to write, read, and manage log entries and configurations through natural language.
Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity.
* Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2
A unified local API gateway providing caching, rate limiting, and full Model Context Protocol compatibility for AI agent integration. It enables users to aggregate multiple API endpoints into a single gateway with built-in observability and customizable eviction strategies.
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.
Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.
Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.
Enables safe, read-only interaction with Kubernetes clusters, allowing users to list resources and fetch logs without any create/update/delete operations.
Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.
An MCP server for managing MCP server registries with health checks, duplicate detection, and configuration portability. It helps prevent MCP sprawl by tracking server health, identifying overlapping tools, and generating portable configurations for different clients.
The Seq MCP Server enables interaction with Seq's API endpoints for logging and monitoring, providing tools for managing signals, events, and alerts with extensive filtering and configuration options.
Enables troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.
MCPWatch: observability for MCP servers. One line instruments any Python MCP server (FastMCP and the low-level Server) and tracks per-tool latency (p50/p95/p99), error rates, silent failures (empty/null returns and isError), and call volume. REST API, CLI, and alert hooks. MIT, no config required.
Detrix is an agentic debugger.
Watch any variable at any line, zero code changes during debugging
Local or cloud - same workflow for Docker containers and remote hosts
Python, Go, Rust - observation points capture values without pausing, without restarting
Enables natural language Kubernetes operations, including smart resource queries, pod root-cause analysis, cross-environment diffs, and manifest generation.
MCP server that enables interaction with Talos Linux clusters via gRPC API, supporting cluster management, monitoring, configuration, and resource inspection.