"Free and open-source GPS without an API" 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.

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 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

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

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.

Enables AI agents to browse and filter experiment runs, retrieve metrics, logs, tables, and artifacts, plot comparisons as PNG images, and download full-fidelity training history for local analysis against a self-hosted Open Train server. It also provides diagnostic tooling that surfaces metric evidence and investigation leads without asserting causality.

Enables endpoint availability monitoring and HTTP health checks for single or multiple URLs.

Enables read-only access to cookieless web analytics aggregates such as sites, visitors, pages, sources, live activity, funnels, and uptime monitoring through OAuth 2.1-secured Streamable HTTP tools.

Multi-machine system monitor with a built-in MCP server that enables AI agents to query health metrics, manage processes, schedule cron jobs, and run diagnostics across local and remote machines.

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 secure access to the LogicMonitor API, enabling AI assistants to manage monitoring infrastructure through natural language commands.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables AI agents to explore and, when writes are enabled, modify a Langfuse deployment — traces, observations, sessions, prompts, datasets, scores, metrics and more — through the full Langfuse public API. Supports Langfuse Cloud in any region and self-hosted instances, including corporate networks that re-sign TLS traffic with their own certificate authority.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

An MCP server that gives coding agents programmatic access to Sumo Logic logs via the Search Job API, enabling issue triage in preview deployments and production without leaving the editor.

Open-source .NET framework and server for Model Context Protocol (MCP) with enterprise OAuth 2.0/OIDC auth, per-tool MFA, OpenTelemetry, and health checks.

MCP-native LLM observability. Query your Spanlens traces, stats, cost anomalies, and savings from Cursor, Claude Desktop, or any MCP client. Open source (MIT).

Local, payload-free AI cost visibility for agents. Track spend by model, route, customer, or tagged work without storing prompt or response bodies.