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

Provides unified project context and monitoring capabilities including project health metrics, build diagnostics, Git integration, and infrastructure validation to initialize development sessions with comprehensive project information.

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.

Connects to MES systems for SOP file upload and abnormal report querying via WorkBuddy.

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

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

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.

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.

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

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.

MCP server for the Zabbix API that provides a daily_brief summary of active problems and category-specific metrics, along with tools to query problems, hosts, and item values.

Provides read-only SQL Server health and diagnostic tools using DMVs, enabling users to query server health, active queries with blocking, and missing indexes through natural language.

Enables AI assistants to review workflow status in n8n instances, including active/inactive counts and workflows with recent errors.

MCP server that allows searching a local notes directory and retrieving live CPU and memory usage.

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 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.

Enables users to ask directly within a Claude Code or Codex chat how much energy and CO2eq their current session or entire project has consumed, estimated locally from session logs with no telemetry or network calls. It also reports everyday-activity equivalents such as kettle boils or washing machine cycles for the resulting figures.

MCP Server for notify to telegram / weixin

A comprehensive MCP server providing OpenStack project management and monitoring capabilities with built-in safety controls and single-project scope.

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 measuring how many tokens each installed MCP server's tool schemas consume in the context window, ranking servers by cost and flagging wasteful schema patterns with estimated savings. It starts each local stdio server, inspects its tools, and reports a verdict without modifying any configuration.

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.

MCP server that enables AI-powered assessment of Active Directory on-premises environments by exposing AD data as queryable tools for LLMs like Claude.

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

Exposes SAP Cloud Integration OData APIs as MCP tools, letting AI assistants list, inspect, create, update, and delete integration packages, iFlows, message processing logs, message stores, log files, security artifacts, and partner directory entries through natural language. All tools are declared in a single JSON config and served by odata-mcp-proxy with OAuth2 authentication via the BTP Destination Service.

Enables AI assistants to converse in plain language with a Wazuh SIEM deployment, querying and aggregating alerts, hunting threats, triaging vulnerabilities, running compliance checks, and executing or rolling back active responses across multi-cluster environments. Works with both cloud and fully local, air-gapped LLM clients while enforcing scoped, audited access to the security tools.

It enables AI clients to monitor real-time CPU, RAM, disk, boot time, and process status, and to securely write reports to a protected local directory.

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 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.

A read-only analytics server that enables AI assistants to list websites and retrieve stats, pageviews, breakdowns, active visitors, and events.

Enables Claude to query and manage workflows in an n8n instance, including listing workflows, checking active status, triggering executions, and reviewing execution history and details.

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.

Enables Claude Code users to inventory the MCP servers, skills, commands, agents and plugins installed on their machine, estimate how many tokens each one adds to every request, and switch them off per project or globally, including across other AI coding tools. It also monitors live sessions to report real token usage and the savings achieved from disabled items.

Gives the model visibility into the same 5-hour session, weekly, and per-model usage percentages shown in Claude Code, along with reset times. It also lets a project cap how much of the weekly limit may be spent via start/check/end budget tools that report OK, LOW, or OVER_BUDGET.

Connects AI assistants to live site data so they can answer questions about crawling, indexing, Search Console performance, keyword gaps and how AI engines describe a brand. Runs technical audits, keyword research, content workflows and client reports directly from the chat.

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.

Enables querying Amplitude analytics data including events, active users, retention, and user profiles through natural language or direct tool calls.