"Methods to Read Data from PostGIS" matching MCP connectors:
Matching Connector Tools:
Give your AI assistant access to real Helm chart data. No more hallucinated values.yaml files.
Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.
Provision, SSH into, run commands on, and manage Linux VPSes from an AI agent. Pay USDC over x402 (Base) or by card over HTTP 402, a running box in under 60s. No signup, no API key to buy. This remote endpoint offers free browse/discovery, quotes, and server status.
Zero-Ops deploy of a private AI workspace to your own VPS — from your AI chat. Free and open-source.
Provides read access to your GKE and Kubernetes resources.
Docker Hub MCP — wraps the Docker Hub v2 API (free, no auth required for public data)
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
The Google Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.
Manage Hostodo VPS infrastructure from MCP clients and AI agents with scoped tokens and audit logs.
Protocol-native energy infrastructure orchestration for AI data centers. Provides 46 MCP tools across 8 grid protocols (IEC-61850, DNP3, Modbus, OCPP, OpenADR, IEEE 2030.5, IEC 60870-5-104, ICCP) with 5 core API primitives: connect, dispatch, settle, comply, and intel. Enables AI agents to programmatically interact with substations, grid interfaces, and energy assets for real-time workload-grid coordination.
Run, build, and validate firmware on virtual hardware from your AI agent. Hardware knowledge corpus.
Manage Rackspace Spot Kubernetes Cloudspaces, node pools, and VMs from your AI assistant.
A paid remote MCP for HyperFrames, built to return verdicts, receipts, usage logs, and audit-ready J
Deploy sims to any screen. Control your displays with Claude.
Deploy sims to any screen. Control your displays with Claude.
Deploy and manage cloud servers from AI agents. Create pods, push code, run commands — all via MCP.