"Repository information for My-FastMCP-Development-Assistant-MCP on GitHub" matching MCP servers:

Enables developers to build production-grade MCP services with dependency injection, zero global state, layered imports, and a sample user-notes tool, resource, and prompt. It includes Testcontainers, Prometheus metrics, Kubernetes probes, and structured logging for testable local and production deployments.

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

A read-only Kubernetes MCP server that enables developers to inspect app status, view pod events, and fetch container logs from dev clusters without requiring full kubectl access.

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 troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.

MCP server that connects LLMs to Kubernetes clusters for troubleshooting, scanning failing pods, diagnosing root causes, and applying guarded fixes or generating manifests via natural language.

Provides comprehensive logging and monitoring capabilities for MCP services with real-time log tailing, advanced search, error analysis, and anomaly detection. Enables centralized log aggregation, correlation tracking, and health monitoring across all MCP ecosystem services.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

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.

Enables AI assistants to monitor and analyze industrial process data from DCS/SCADA systems via MCP protocol, with domain expert knowledge for anomaly detection and recommendations.

Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.

Enables LLMs to query real job data and summarize backend job failures using MCP tools backed by a SQLite database.

MCP servers for real-time development monitoring and interactive pair programming.

A Model Context Protocol server that enables retrieving and analyzing Sentry issues, including stacktraces and debugging information.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Asynchronous MCP server for unified multi-platform network infrastructure management, providing 97 tools across 10 connectors including SSH, MikroTik, Palo Alto, Aruba, Graylog, LibreNMS, Cisco APIC/NDFC, and Panorama.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

Enables read-only system diagnostics on approved Linux hosts over SSH, with allowlisted commands, bounded output, and secure log access.

Enables simulation of production incident alerts and resolution by exposing an active alerts resource and a tool to restart services with simulated success or failure outcomes.