"How to implement Active Directory authentication in a project" matching MCP servers:

It enables AI agents to securely perform directory administration, automation, security auditing, health diagnostics, and compliance reporting with strict guardrails, write-approval workflows, and immutable audit logs.

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.

A comprehensive project management and workflow tracking system that integrates with Claude Code via MCP, automatically capturing sessions, tools, agents, and project tasks into a centralized dashboard and database.

Enables AI agents to investigate incidents by listing services and dependencies, searching redacted logs, summarizing metrics, checking recent deploys, and producing ranked timelines with scoped tokens, validation, rate limiting, and audit logging.

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.

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

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 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.

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

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Enables read-only triage of Microsoft Entra ID sign-in and audit logs through fixed tools for sign-in failure analysis, user lookup, directory audits, and daily briefs.

A read-only server that enables AI agents to triage Kubernetes CronJobs in a single tool call: whether runs happened and stayed on schedule, whether durations are trending slower or overrunning, which jobs have silently stopped succeeding, and why a given run failed, with evidence and stated basis for each verdict. It also lists active runs and recent failures while enforcing namespace allowlists and no write access.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

Ask your AI agent about your MCP servers: which tools fail, how a release compares, what clients look for and do not find. Reads from mcpspan with a read token.

Enables AI assistants and MCP clients to analyze offline Oracle AWR/ASH reports in HTML or text across Oracle 10g–23ai, including single-instance and RAC global reports, returning report type, version, active sessions, load profile, top waits and SQL with version-aware tuning advice plus a prioritized top-3 summary, all locally without an Oracle client or database connection.

Enables AI agents to inspect a live Celery deployment over RabbitMQ or Redis — checking which workers are responding, their pools, concurrency and consumed queues, and how many messages are backed up in each queue — so agents can diagnose stuck or unrouted tasks. Read-only by default, with broker credentials masked in all output.

Executes constrained, read-only Prometheus queries for instant metrics, active alerts, and target health, with bounded resource usage and audit records.

Enables MCP clients to query and manipulate a Wazuh SIEM deployment through its manager, Indexer, and dashboard REST APIs, covering agents, alerts, vulnerabilities, rules, decoders, active response, and content promotion.

Enables AI agents to access real-time Windows PC context including active window, system performance, screen time, productivity analytics, and historical usage through MCP tools.

Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.

Enables MCP clients to interact with a fictional bank through remote tools, including mock banking operations, OAuth 2.1 authentication, and a live X-ray dashboard for observing session activity.

Enables troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.

Gives AI coding agents read-only access to Grafana's Loki logs, Prometheus metrics, Tempo traces and active alerts from within a project, using per-project context declared in the repo and one-command switching between test and prod environments. Credentials are discovered by parsing shell rc files directly, so it works even when spawned as a non-interactive MCP client process.

Enables natural language interaction with Wazuh SIEM for alert querying, threat hunting, vulnerability scanning, and active response actions.

Enables MCP clients to list recorded runs and read declared plan artifacts — plans, journals, and outputs — from a local runs directory over stdio, with traversal and undeclared-file protections.

Enables querying WhaTap monitoring data using MXQL (Metrics Query Language) through Claude Code, providing project management, secure authentication, and natural language to MXQL query translation capabilities.

Provides Claude AI assistants with focused monitoring tools for n8n workflow execution analysis, including active workflow listing, execution history with KPIs, and detailed failure information.

Enables simulation of production incident alerts and resolution by exposing an active alerts resource and a tool to restart services with simulated success or failure outcomes.

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.

Exposes Umami analytics (Cloud or self-hosted) as read-only tools for querying website stats, pageviews, metrics, and active visitors.

Enables infrastructure health overviews, detailed host metrics, active alert retrieval, and optimization recommendations through MCP tools.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Enables AI assistants to execute PromQL queries and discover metrics within AWS Managed Prometheus (AMP) using SigV4 authentication. It provides tools for instant and range queries, label management, and metric discovery in secure, VPC-isolated environments.

Provides read-only monitoring of Apache Airflow DAGs, including listing active DAGs, fetching recent runs, and analyzing execution history and performance metrics.

Enables users to monitor and query Zabbix infrastructure through natural language by providing access to current problems, active triggers, and system health status via the Zabbix API.

Enables interaction with Dynatrace Grail and API endpoints by executing DQL queries, retrieving logs, reporting active problems, and querying metrics.

In-cluster MCP server for read-only diagnostics of Grafana, Prometheus, Alertmanager, and Loki, enabling metric queries, alert listings, and log queries through Grafana datasource proxies with Kubernetes RBAC authentication.

MCP server to start, monitor, search, and detect errors in logs from any project, even those without log files.

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