"A server for finding real estate in France" matching MCP servers:

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

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.

Self-hosted Nightingale (n9e) includes a native Streamable HTTP MCP server at /mcp for querying alerts, rules, metrics, logs, hosts and dashboards with the caller's existing permissions. Users deploy the Nightingale server themselves; the implementation and deployment documentation are in the main repository, and the official website is https://n9e.io.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

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.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

Provides Model Context Protocol access to the Dynatrace platform API, letting AI agents run live queries against observability, security, and platform data and manage a Dynatrace environment. It is hosted remotely by Dynatrace, so MCP hosts can add it by name from the official registry without installing anything.

A remote, Dynatrace-hosted MCP server that gives AI agents live API access to your Dynatrace environment. It enables querying and analyzing observability, security, and platform data — such as DQL queries, logs, traces, problems, and dashboards — so agents can act on production context instead of static knowledge.

MCP server for administering a Zigbee2MQTT estate, enabling mesh health monitoring, device management, firmware updates, pairing, binding, and reporting via natural language.

Tracks AI agent token usage and spending in real time, with budget alerts, per-task cost breakdown, and a visual dashboard.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Provides read-only observability and operational insight into a MuleSoft Anypoint Platform estate, enabling natural-language queries for application logs, archived log search, Runtime Manager inventory, API Manager instances, and Exchange assets using your own credentials.

Real User Monitoring for Core Web Vitals. Query LCP, INP, and CLS field data from real visitors.

Enables real-time AI behavioral drift monitoring and detection for Claude Code, tracking shifts in model behavior across 11 major models with tools for scorecards, version changes, and compliance reports.

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

Lets AI agents inspect Kubernetes clusters in plain English, exposing read-only tools for pods, deployments, services, events, and logs, with mock and real backend support.

Enables secure MCP traffic by filtering threats with a 3-stage detection pipeline, applying RBAC policies, and redacting sensitive data in real-time via an SSE-inspecting proxy.

Give your AI coding agents the superpower to observe your NestJS application's runtime state in real-time.

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

Provides tools to search Splunk logs, inject test data, and send triage emails, enabling AI-driven incident investigation.

Role-aware MCP server over real HPC and cloud log corpora (BGL, OpenStack, Zookeeper) in SereneDB, where every answer cites the exact SQL that ran, backed by a tamper-evident, hash-chained evidence ledger.