"A guide to understanding AI agents" matching MCP servers:

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

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.

Integrates Claude Desktop with Azure AI Search, allowing users to query search indexes using keyword, vector, or hybrid search methods.

Enables AI agents to access Cloudflare Workers AI for serverless LLM chat completions, text embeddings, and image generation via MCP tools.

Intelligent AI routing and integration platform for seamless provider switching

Deterministic AI data-center design engine exposed as MCP tools for sizing, validation, and physical layout. Supports NVIDIA Hopper, Blackwell, and Vera Rubin with anonymous access to the remote engine.

An MCP server that enables running commands against a ServiceNow instance via its REST APIs, including Table, Aggregate, Attachment, Import Set, Batch, CMDB, Service Catalog, Change Management, and Knowledge APIs.

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.

Cloudeval AI provides cloud evaluations and reviews through MCP, with project context and reports for Azure and static AWS CloudFormation evaluation (beta). Includes a read-only toolset; requires a Cloudeval account and hosted services, and the public CLI uses a custom proprietary license.

Provisions Google Analytics 4 for local AI/web projects by creating properties and web data streams, injecting gtag snippets, and saving configuration.

Enables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.

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.

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

An MCP server that gives an AI agent controlled access to a Selectel cloud account: OpenStack cloud servers, S3 object storage, and account billing.

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

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.