"A search for date and time" matching MCP servers:

这是面向智能运维场景的 MCP 工具服务，让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程，从而支撑自动故障排查与根因分析。

MCP server that provides read access to Plausible Analytics data with natural-language date resolution, enabling users to query analytics like 'yesterday' or 'last week' without needing to know exact date formats.

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

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Enables AI assistants to query structured Seq logging events, search logs by date ranges and signals, convert natural language into strict Seq filter syntax, run analytical SQL queries, and monitor live log streams.

Enables MCP clients to interact with a local AI agent through Ollama, providing tools for checking weather, current time, and available models, while tracing calls to Langfuse.

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.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

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.

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.

Ships only the MCP server, not the recorder. Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git index. None of that survives a container boundary, so orca record inside here would watch an empty namespace. What does travel is the read side: the six MCP tools serve runs that already exist on disk, so a client mounts its .orca directory and r

Enables users to log AI tool activity without conversation text and contribute back only user-approved, small-cell-suppressed counts through a local MCP interface.

It enables agents to discover Rapid7 InsightIDR log sets and logs, run LEQL searches and analytics, and follow paginated results for natural-language investigations.

The Wireshark for the Model Context Protocol (Reticle) intercepts, visualises, and profiles MCP JSON-RPC traffic in real time — designed for microsecond-level overhead.

A live post-mortem debugger MCP server for Home Assistant that lets AI agents list captured exceptions, walk traceback frames, read local variables, and optionally evaluate Python in the context of a captured frame for true post-mortem debugging.

InfluxDB-v1-MCP is a powerful Model Context Protocol (MCP) interface specifically designed for InfluxDB v1.x, enabling AI assistants to intelligently manage and query time-series databases.

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

Aggregates logs from multiple processes and provides an MCP server for AI agents to access, search, and manage logs in real-time.