mcp-use Cloud
Build and deploy MCP agents with zero friction
mcp-use Cloud Overview
mcp-use Cloud is a powerful platform for building and deploying MCP (Multi-Component Processing) agents. It provides developers with tools to spin-up and aggregate MCP servers through a single endpoint, eliminating deployment friction. The platform offers managed MCP gateways that handle routing, authentication, and load-balancing for all your servers, whether they're hosted, ephemeral, or on-prem. With built-in OAuth, ACLs, metrics, and tracing, mcp-use provides production-grade observability from day one. The platform is particularly valuable for developers building AI products and services that require complex processing pipelines.
mcp-use Cloud Screenshot
mcp-use Cloud Official screenshot of the tool interface
mcp-use Cloud Core Features
MCP Gateway
The managed MCP gateway provides a single endpoint for every MCP server, handling routing, authentication, and load-balancing. It supports hosted, ephemeral, or on-prem servers with built-in OAuth, ACLs, metrics, and tracing for comprehensive observability.
Agent SDK
The open-source mcp-use library allows you to turn any MCP call into an AI agent with just 3 lines of code. The SDK automatically pulls MCP server configurations and streams results out of the box, supporting both Python and TypeScript.
Server Management
Deploy fully managed MCP servers in the cloud, sandbox local VMs on demand, or proxy third-party servers behind the gateway. All servers are managed through a unified dashboard for complete control.
Zero-Setup Agents
Create and interact with MCP agents instantly using the AI-powered chat interface, requiring no configuration or deployment setup. This enables rapid prototyping and testing of MCP workflows.
Production-Grade Infrastructure
The platform provides built-in caching, memory management, monitoring, and metrics for production-ready MCP implementations. The control plane gives you visibility and management of all your MCP infrastructure in one place.
mcp-use Cloud Use Cases
AI Content Generation
Create marketing content automatically by connecting MCP agents to various content generation tools and models, streamlining your content creation pipeline.
Data Processing Pipelines
Build complex data processing workflows by chaining multiple MCP servers together through the gateway, with built-in monitoring and error handling.
Rapid Prototyping
Quickly test new AI product ideas by spinning up temporary MCP servers and agents without deployment overhead.
How to Use mcp-use Cloud
Install the mcp-use library using pip (Python) or npm (TypeScript) to get started with the SDK.
Initialize the MCP client and connect to your server pool using either a local script or remote endpoint.
Configure your agent by specifying the model provider, API keys, and any tools you want to use.
Create your MCP agent instance with the configured client and model parameters.
Run queries through your agent, which will automatically handle tool calls and process results through the MCP gateway.