"Learning to Create an Expert Python Program to Exit GitHub" matching MCP servers:

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.

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.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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.

Real-time GitHub Actions observability through VS Code with GitHub Copilot, providing DevOps metrics and interactive dashboards.

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

Enables multi-agent system auditing with seven-layer analysis, cost governance, compliance mapping, and watchdog monitoring. Offers tools for audit execution, cost analysis, report verification, regulation lookup, remediation suggestions, and fix tracking.

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.

Record Python/Rust/TypeScript program runs to local SQLite; query call trees, exceptions, and value flow over MCP — refuses rather than guesses. Not the unrelated Telegram sensorium-mcp.

An MCP server that surfaces scheduled-job state and detects silent failures (exit 0 but no useful output) for cron, systemd timers, and OpenClaw schedulers, enabling AI agents to query job health and overdue status directly.

MCP server for Python JSON logs

Enables local LLM clients to capture and analyze network traffic using Wireshark's CLI tools, providing packet summaries, protocol hierarchies, conversations, endpoints, expert info, and stream reassembly without shell access.

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 AI agents to check real-time status, uptime, and incidents for 200+ popular APIs (Stripe, OpenAI, AWS, GitHub, Twilio, etc.) through read-only, no-authentication tools.

Enables AI agents to trace Python code execution in real time via PEP 669, exposing call trees, variable deltas, and async context through MCP tools.

AgentVision is a debug flight recorder MCP server that watches a target program, captures its window and logs, and exposes time-aligned, verified evidence through 90 MCP tools so AI agents can debug running programs without hallucinating.

An MCP server for managing OpenSearch Dashboards, enabling AI assistants to create, manage, and inspect dashboards, visualizations, saved objects, and plugin features.

An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.

Enables an AI agent to investigate AcmeShop operational data and create incidents through a mock REST API using a local stdio transport.