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 interact with Semaphore UI for managing Ansible, Terraform, and other automation workflows through project, task, template, and inventory management.
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.
An MCP server and terminal UI that orchestrates Cloudflare, Namecheap, and Fleet from a single interface, enabling domain onboarding with automatic DNS migration and security hardening.
A boilerplate for building MCP servers on Cloudflare Workers with built-in OAuth 2.1 authentication, Stripe billing integration, and OpenAI Apps SDK UI support.
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.
An MCP server for SAP Cloud Integration (CPI) that exposes OData APIs as MCP tools, allowing AI assistants to manage integration content, monitor message processing, and configure security artifacts through natural language.
MCP server that lets an AI agent manage Proxmox VE in natural language, with policy-driven security, read-only mode, two-step confirmations, and audit logging.