"Developing an API using NestJS, Prisma, and PostgreSQL" matching MCP servers:

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

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

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.

Enables AI assistants to perform read-only PostgreSQL DBA analysis and monitoring through natural language, covering performance, bloat, locks/deadlocks, autovacuum, and schema inspection across PostgreSQL 12-18 without required extensions.

Enables AI assistants to perform read-only PostgreSQL DBA work across versions 12–18, including performance analysis, slow query identification, bloat detection, lock and deadlock monitoring, autovacuum and schema inspection, and replication/WAL checks via natural language. Works with regular user permissions on RDS/Aurora without requiring any extensions, while optionally leveraging pg_stat_statements and pg_stat_monitor for deeper query analytics.

Enables AI assistants to monitor and administer PostgreSQL 12-18 through natural language, covering performance and slow-query analysis, table bloat detection, lock and connection monitoring, replication and WAL status, and VACUUM/autovacuum and schema inspection. It works read-only out of the box with automatic version detection and optional extension-enhanced query analytics.

Enables AI assistants to perform read-only PostgreSQL DBA and monitoring tasks, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection across PostgreSQL 12–18. It supports natural-language queries against production-safe, RDS/Aurora-compatible connections, with optional query analytics via pg_stat_statements or pg_stat_monitor.

Enables natural-language monitoring and administration of PostgreSQL databases, covering performance analysis, bloat detection, lock and deadlock monitoring, autovacuum intelligence, and schema inspection. It works with PostgreSQL 12-18 and can run without extensions, with optional extensions for advanced query analytics.

Enables AI assistants to perform PostgreSQL database operations and monitoring through natural language, including performance analysis, bloat detection, lock and deadlock monitoring, autovacuum and schema inspection across PostgreSQL 12-18.

Enables AI assistants to inspect and monitor PostgreSQL 12-18 databases through natural language, covering performance analysis, slow-query identification, bloat and lock detection, autovacuum health, replication/WAL status, and schema exploration. All operations are read-only and work without requiring any extensions, though pg_stat_statements and pg_stat_monitor optionally enhance query analytics.

Enables AI assistants to perform read-only PostgreSQL DBA operations and monitoring through natural language, including performance and slow-query analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection, and maintenance recommendations across PostgreSQL 12–18.

Enables AI assistants to inspect and monitor PostgreSQL databases with read-only DBA tools for performance analysis, bloat detection, locks/deadlocks, autovacuum, schema discovery, replication, and maintenance recommendations.

Enables AI assistants to monitor and administer PostgreSQL 12-18 databases through natural language, covering performance and slow-query analysis, table bloat detection, connection and lock monitoring, autovacuum and maintenance recommendations, and schema discovery. All operations are read-only and work with regular user permissions, requiring no extensions unless optional query-analytics features are desired.

Enables AI assistants to perform PostgreSQL database operations, monitoring, and management through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection, with no extensions required.

Enables AI assistants to perform PostgreSQL database operations, monitoring, and management through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum, and schema inspection. Supports PostgreSQL 12-18 with read-only production-safe tools and optional extension-enhanced query analytics.

Enables AI assistants to perform PostgreSQL database operations, monitoring, and management through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection, and maintenance recommendations across PostgreSQL 12-18.

Enables natural-language PostgreSQL operations and monitoring across PG 12-18 without requiring extensions, covering performance analysis, slow-query identification, bloat detection, lock and connection monitoring, autovacuum inspection, replication/WAL status, and schema relationship discovery. All operations are read-only and production-safe, working with regular user permissions on RDS/Aurora as well as self-hosted instances.

Enables AI assistants to perform PostgreSQL operations and monitoring through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum inspection, schema discovery, and maintenance recommendations with production-safe read-only tools across PostgreSQL 12–18.

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2

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 secure, AI-driven PostgreSQL database administration, observability, and querying with support for extensions like PostGIS and pgvector, connection pooling, and advanced tool filtering.

An MCP server that enables interaction with Google Cloud Logging API, allowing users to write, read, and manage log entries and configurations through natural language.

A unified local API gateway providing caching, rate limiting, and full Model Context Protocol compatibility for AI agent integration. It enables users to aggregate multiple API endpoints into a single gateway with built-in observability and customizable eviction strategies.

Enables endpoint availability monitoring and HTTP health checks for single or multiple URLs.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.

An enterprise AI control plane with an MCP gateway for connecting agents to tools, enforcing identity-based access and security policies, and recording activity.

Provides secure access to the LogicMonitor API, enabling AI assistants to manage monitoring infrastructure through natural language commands.

Enables AI agents to explore and, when writes are enabled, modify a Langfuse deployment — traces, observations, sessions, prompts, datasets, scores, metrics and more — through the full Langfuse public API. Supports Langfuse Cloud in any region and self-hosted instances, including corporate networks that re-sign TLS traffic with their own certificate authority.