发现我们为 cloud infrastructure 精心策划的 MCP 服务器集合。浏览 1497 个服务器,找到满足您需求的完美 MCP。
Provides deployment infrastructure and server implementations for Columbia's Model Context Protocol (MCP) servers.
Enables natural language interaction with Upstash Developer APIs for managing databases and related resources using Claude Desktop or any MCP client.
Serves resume data via the Model Context Protocol (MCP) using Cloudflare Workers and Durable Objects.
Deploys a remote Model Context Protocol (MCP) server on Cloudflare Workers without requiring authentication.
Deploy a Model Context Protocol server on Cloudflare Workers without requiring authentication.
Calculates approximate hardware requirements for dedicated search nodes on MongoDB Atlas, supporting both lexical and vector search use cases.
Enables AI agents to execute code in a sandboxed Google Cloud Functions environment.
Enables AI assistants to securely execute Azure CLI commands for managing cloud resources.
Facilitates building and deploying custom remote servers to the cloud using Azure Functions with Python.
Connects large language models (LLMs) to various Aiven services like PostgreSQL, Kafka, and OpenSearch to facilitate full-stack solution building.
Provides an interface for Large Language Models to interact with Aiven services like PostgreSQL, Kafka, and OpenSearch, facilitating full-stack solution development.
Transforms complex GitHub Actions Runner Controller (ARC) operations into conversational AI interactions for streamlined management.
Deploys a remote Model Context Protocol server on Cloudflare Workers for seamless AI agent integration.
Enables AI assistants to interact with the Alibaba Cloud Yunxiao platform, managing various DevOps processes from code to deployment.
Analyzes application installation requirements from Git repositories and validates them against OpenShift/Kubernetes cluster resources.
Enables LLMs to explore and execute any OVH API endpoint securely through a sandboxed JavaScript environment.
Manage Google Cloud Scheduler jobs by creating, listing, updating, pausing, resuming, and deleting scheduled tasks via a Model Context Protocol (MCP) interface.
Provides AI agents with a secure, stateful environment to execute Python and JavaScript code, acting as a direct replacement for Azure Assistants Code Interpreter.
Provides an enterprise-grade server for orchestrating and managing long-running AI agent tasks across sessions and memory boundaries.
Enables multiple AI companions to communicate in Discord using a single bot token, appearing with their own names and avatars.
Scroll for more results...