Discover our curated collection of MCP servers for cloud infrastructure. Browse 1614 servers and find the perfect MCPs for your needs.
Enables programmatic management of Supabase projects and organizations through a standardized interface.
Demonstrates implementation and usage of Anthropic's Model Context Protocol (MCP) with AWS Bedrock.
Provides a REST API for managing VMware ESXi/vCenter virtual machines using the Model Control Protocol.
Manages Appwrite projects through a Model Context Protocol server, offering tools for databases, users, and more.
Enables natural language control of Upstash resources through the Model Context Protocol.
Enables AI assistants to interact with and extract information from an Unraid server through the official Unraid GraphQL API.
Enables AI assistants to query and analyze Azure Data Explorer databases through standardized interfaces.
Connects Claude Desktop to Azure AI Search capabilities through a Model Context Protocol (MCP) server.
Provides AI assistants like Claude with access to ROADRecon Azure AD data for security analysis.
Manages containerd CRI interfaces using the Rust Model Context Protocol (RMCP) library.
Provides examples for integrating the Model Context Protocol with AWS services.
Enables Large Language Models to securely query and analyze Azure Cosmos DB data through a standardized interface.
Enables users to chat and query their documents directly from IDEs and other MCP-compatible clients.
Provides an MCP server for managing Alibaba Cloud RDS services via OpenAPI.
Enables AI assistants to interact with Kubernetes clusters using natural language.
Simplifies the deployment of Model Context Protocol (MCP) servers by providing a purpose-built CI/CD platform.
Deploys a complete AWS backend infrastructure for retrieval-augmented generation applications, integrating with Gemini Pro and a Streamlit UI.
Connects Model Context Protocol (MCP) clients to Gemini Cloud Assist APIs, enabling natural language management and troubleshooting of Google Cloud environments.
Gain comprehensive visibility into Apache Iceberg-based data lakehouses, displaying detailed metadata and structural information.
Provides a queue-based actor framework for orchestrating AI/ML workloads on Kubernetes.
Scroll for more results...