"NestJS Framework for Building Backend Applications" matching MCP servers:

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

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.

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.

Runtime constitutional verification for AI answers — claim extraction with reasoning chains, Epistemic Confidence Score (ECS), 7-angle Glassbox Court red team, constitution compilation, Trust Card assembly, and deterministic SHA-256 audit logs.

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-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.

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.

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

Unified observability gateway for AI agents — one MCP server for Prometheus, Loki, and any backend.

MCP server for Langfuse observability. Query traces, debug exceptions, analyze sessions, and manage prompts and datasets for your LLM applications.

Enables AI agents to investigate backend incidents by executing runbooks that gather evidence from observability and storage systems.

Exposes Spark History Server data as tools for AI agents, enabling natural language querying of Spark applications, jobs, stages, and performance metrics.

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 coding agents to debug backend requests by providing tools to list, view, wait for, diagnose, and clear request traces.

A minimal guardrails framework for AI agents, acting as an MCP proxy to enforce policies, approvals, and audit logging on tool calls.