Mcp-use
Why Choose Mcp-use?
Choose this if you’re a dev team wanting an open-source platform to build and deploy AI agents quickly. It’s flexible, supports multiple deployment options, and comes with tools to manage your AI servers without fuss.
Open-source platform for building and deploying AI agents and MCP servers.
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Mcp-use Introduction
What is Mcp-use?
mcp-use is an open-source platform that provides devtools and cloud infrastructure to help development teams quickly build and deploy custom AI agents using MCP (Model Context Protocol) servers. It offers an SDK for creating AI agents, a registry for discovering community-built servers, and a managed gateway for routing, authenticating, and load-balancing MCP servers. The platform aims to simplify the process of building, discovering, and deploying MCP servers and AI agents, supporting various deployment environments including cloud, local VMs, and third-party services.
How to use Mcp-use?
Users can get started by installing the mcp-use SDK via `pip install mcp-use` or `npm install mcp-use`. With the SDK, developers can create AI agents by connecting to MCP servers, using any model provider (e.g., Claude). The platform allows spinning up and aggregating MCP servers through a single endpoint. Users can deploy fully managed MCP servers in the mcp-use cloud, sandbox local VMs, or proxy third-party servers behind the gateway, all managed from a single dashboard. An AI-powered chat interface is also available for instant testing and interaction with MCP agents.
Why Choose Mcp-use?
Choose this if you’re a dev team wanting an open-source platform to build and deploy AI agents quickly. It’s flexible, supports multiple deployment options, and comes with tools to manage your AI servers without fuss.
Mcp-use Features
AI API
- ✓Open-source SDK for building custom AI agents
- ✓Cloud infrastructure for deploying and managing MCP servers
- ✓Managed MCP Gateway for routing, authentication, and load balancing
- ✓Registry for discovering community-built MCP servers
- ✓Support for various deployment options (cloud, VM, third-party)
FAQ?
Pricing
Pricing information not available