"A guide for executing queries in a GCP PostgreSQL database" matching MCP servers:

Enables AI assistants to interact with Google Cloud Platform services for log analysis and root cause investigation. Provides tools to query Cloud Logging, detect error patterns, and perform real-time log streaming across multiple GCP projects.

Enables comprehensive PostgreSQL database monitoring, analysis, and management through natural language queries. Provides performance insights, bloat analysis, vacuum monitoring, and intelligent maintenance recommendations across PostgreSQL versions 12-17.

Enables AI agents to interact with PostgreSQL databases over HTTP/JSON-RPC, supporting SQL queries, schema introspection, table/index analysis, EXPLAIN query planning, role and privilege inspection, and database monitoring.

Full-featured MCP server that exposes 36 tools for interacting with PostgreSQL databases, covering schema introspection, query execution, data exploration, performance monitoring, security auditing, and maintenance.

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 AI clients to safely query PostgreSQL or SQLite databases read-only through AST-validated guardrails, schema introspection, and statistical table profiling. It returns results as Markdown tables, JSON audit reports, and database health checks.

MCP server for unified SQL database access, supporting multiple databases with schema discovery, caching, and safety controls.

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

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

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

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.

Shows your current Claude Desktop activity as Discord Rich Presence, including model, status, usage, and subscription info.

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 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.

Gives your AI assistant full control of a Discord server: 148 tools for chat, moderation, automod, events, and administration, up to building a complete community server from one paragraph. Every destructive action previews first and waits for your confirmation.

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.

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

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.