"Informational MCP Servers with Croissant Dataset Format Support" matching MCP servers:

A read-only MCP server exposing SLURM, GPFS, Prometheus (node exporter + DCGM GPU metrics) and generic Elasticsearch exploration as diagnostic tools for LLM-based HPC support assistants.

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.

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 Arize Phoenix enabling AI agents to perform LLM tracing, evaluation, and dataset management for automated quality assurance.

An MCP server for querying Observe.com logs using OPAL, with tools for dataset discovery, schema inspection, and log searching.

Provides tools to search, query, and visualize Prometheus metrics, returning results in JSON format for AI analysis.

Enables AI agents to investigate very large log files with constant-memory streaming, offering format overviews, filtered searches, error clustering, timelines, request tracing, and window comparisons across plain, gzipped, and rotated logs.

Enables provider-neutral policy enforcement, identity, persistent storage, and telemetry collection for reinforcement learning, evaluation, analytics, replay, and downstream dataset generation across standalone applications and agent systems.

An AI-powered Power BI dataset health monitor that connects Claude to a simulated Power BI tenant for running health checks, diagnosing failures, and prioritizing fixes.

Enables AI agents and MCP clients to query trace, session, exception, prompt, dataset, score, and metric data for enhanced debugging and observability.

Enables governed agent access to Cortex XSIAM security operations APIs, including XQL log search, issues, cases, endpoints, and assets, with dataset authorization and optional identity-based access control.

Enables AI agents to query and debug Langfuse traces, sessions, and exceptions locally, with route-decision tools, metrics, prompt and dataset access, plus compact or file-dump output for token control.

Enables AI agents and developers to query trace, session, exception, routing, prompt, dataset, score, and metrics data for debugging, triage, and observability, with selective tool loading and a read-only mode.

Enables AI agents to query and debug trace, session, exception, prompt, dataset, score, and metric data, with selective tool loading and read-only operation for safer local observability workflows.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

Tells an agent what went wrong with its own Ollama calls, in sentences with the fix: lost prompt cache and where the prompt stopped matching, context overflow, a model running partly on CPU, tool schemas crowding the prompt. Also the last turn in numbers and which local models fit in video memory. Local, read-only, nothing leaves the machine.

Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.

MCP server for measuring web performance with Google PageSpeed Insights, providing median scores with uncertainty and real-user data. It offers tools for scores, diagnostics, and comparisons to identify regressions.

Minimal MCP server that integrates with Graylog, enabling agents to search, analyze, and inspect log messages across streams, discover fields and streams, and query multiple Graylog instances.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Uptime monitoring for websites, APIs, SSL certificates, domain expiry, ping and TCP/UDP ports. 15 tools to list, create, pause and delete monitors, pull incident timelines with error codes, and read hourly or daily uptime and response-time statistics.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

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.

Enables interaction with OPNsense firewalls through MCP tools for managing firewall rules, interfaces, DHCP leases, and system monitoring.

MCP server that transforms raw log query results into structured incident reports (Markdown, JSON, HTML) with correlation to git commits and tickets.

Enables monitoring and analysis of agent goal achievement and failures across sessions, repos, and tools, with detailed views and tracing.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.