"Non-Docker Implementation of Jira with MCP" matching MCP servers:

Enables read-only inspection and narrowly scoped maintenance of a local Docker Desktop environment, covering containers, images, logs, stats, Compose status, and Scout vulnerability/SBOM data, plus limited actions such as image pulls, container restarts, dangling-image pruning, and allowlisted Compose redeploys, all without exposing the raw Docker socket to the client.

Enables Claude to inspect and manage Docker containers locally, including listing containers, fetching status and logs, and checking system health. It also supports safely restarting whitelisted containers through a two-step confirmation flow with an audit trail.

Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.

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.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

MCP server for IBM QRadar SIEM that consolidates 728 REST API endpoints into 4 intelligent tools, enabling natural language interaction for security tasks like managing offenses, assets, rules, and reference data.

Read-only observability MCP for Windows, WSL, Docker, and WSLC.

Enables debugging of distributed transactions by continuously ingesting Docker container logs, indexing them by trace/request ID, and exposing MCP tools to search, tail, and correlate logs across services.

Provides system monitoring tools for VPS including CPU, memory, disk, network ping, top processes, and Docker status, with read-only architecture and security features.

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

Governed Docker + Portainer container-host operations (non-Kubernetes) — restart-loop, resource-pressure, and image/volume-bloat RCA, with guarded lifecycle writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.

Honeycomb MCP (Model-Controller-Presenter) Server implementation

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

Enables AI assistants to interact with local Docker containers, Kubernetes clusters, and system logs using the Model Context Protocol.

MCP server that provides AI agents with comprehensive access to VMware vSphere operations, including VM management, monitoring, and vSAN read-only monitoring, through a secure Docker environment.

An MCP server implementation that enables dynamic configuration of OpenTelemetry Collectors, allowing users to add, remove, and configure receivers, processors, and exporters through MCP tools.