"Ko-fi" matching MCP servers:

Intelligent AI routing and integration platform for seamless provider switching

An MCP (Model Context Protocol) server that lets AI agents manage Power BI workspaces, datasets, and refreshes via natural language.

A Model Context Protocol (MCP) server that exposes the EasyDeploy public REST API as tools for Claude, Cursor, Claude Code, and other MCP clients.

Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.

Enables AI assistants to discover, explore, and query Formula 1 data stored in AWS, using Athena and Glue for schema inspection, sample data, and custom analytical queries.

A high-performance MCP server for Ubiquiti UniFi Dream Machine (UDM Pro/SE) and UniFi OS Cloud Gateways, connecting directly to the local REST API using native API keys to provide 40 tools for managing Wi-Fi, VLANs, firewall rules, port forwarding, switch ports, guest vouchers, QoS, clients, and devices—all with 2FA bypass and ultra-low latency.

Enables AI-powered image and video analysis using Google Gemini and Vertex AI models. Supports analyzing single or multiple images, detecting objects with bounding boxes, and video content analysis through natural language prompts.

Enables AI agents to interact with the app via MCP tools and resources, supporting self-improvement through goal-setting and metrics tracking on Cloudflare Workers.

Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.

Enables integration with Google Cloud Vertex AI Search for enterprise search capabilities through a stdio-based MCP server.

An MCP server for Kvindo Cloud that lets AI clients list, inspect, create, update, and delete cloud resources (VMs, volumes, Kubernetes, etc.) via natural language. Read-only by default, with write/delete operations gated by explicit opt-in environment variables.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

Exposes SAP AI Core APIs as MCP tools, enabling AI assistants to manage AI Core lifecycle and administration through natural language.

Enables AI assistants to manage SAP Cloud Integration (CPI) landscapes through natural language by exposing CPI OData APIs as MCP tools.

Analyzes DevOps findings to automatically recommend and generate AWS Fault Injection Simulator (FIS) experiment templates. It helps teams validate system resilience by mapping reported issues to specific chaos engineering actions across AWS services.

Enables interaction with Azure AI Agent Service by automatically discovering agents and creating MCP tools for querying and managing agent workflows.

Enables AI agents to dynamically spawn, route to, and manage ephemeral containerized sandboxes on Kubernetes without requiring Custom Resource Definitions or cluster-level operators.

Enables interaction with Azure AI Foundry services for model exploration, deployment, and performance evaluation. It provides tools for managing knowledge bases via AI Search Service, executing fine-tuning jobs, and orchestrating AI agents through natural language.

Enables AI assistants to generate images using Cloudflare Workers AI models directly through the Model Context Protocol. It supports various models like Flux and Stable Diffusion, providing seamless image generation and storage via Cloudflare R2.

Provides MCP multi-cluster Kubernetes management and operations. It can be integrated as an SDK into your own project and includes nearly 50 built-in tools covering common DevOps and development scenarios. Supports both standard and CRD resources.