"Using Python REPL from an MCP server on Windows" matching MCP servers:

Read-only MCP server for diagnosing Windows crashes, stability, and gaming performance by reading event logs, crash dumps, hardware inventory, performance counters, and registry settings.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

An MCP server that enables AI assistants to manage, monitor, and diagnose Windows systems through 42 tools across 8 modules, including services, event viewer, task scheduler, processes, network, diagnostics, observability, and safety features.

Enables AI agents to access real-time Windows PC context including active window, system performance, screen time, productivity analytics, and historical usage through MCP tools.

Enables read-only observability of Windows systems, exposing CPU, memory, storage, service, and health information through Model Context Protocol tools.

MCP server for safely exposing SQL Server database capabilities to LLM clients, with read-only mode, security features, and observability.

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of systems using Langfuse.

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

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.

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

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 remote log searching, tailing, and file reading across servers via MCP tools, with pluggable execution via SSH, pyinfra, or local commands.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

An MCP server that automatically instruments Python AI agents with the ioa-observe-sdk, adding OpenTelemetry-based tracing, metrics, and logs with zero manual effort.

An on-call agent for data incidents, built on a bio-inspired context protocol. It triages data quality and freshness issues using DataHub, computing severity, blast radius, and ownership from the catalogue before generating prose.

Enables forensic analysis of Windows event logs (.evtx) using Hayabusa, providing tools for timeline generation, threat hunting, and rule updates via MCP.

See which AI agent and MCP server talks to what on Windows, with a rule-based security verdict

MCP server for Python JSON logs

A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.

An MCP server that provides AI assistants with real-time access to Windows internals including processes, kernel traces, event logs, services, drivers, and PE analysis.