mcp-use
mcp-use is a platform and open source library for building, deploying, and managing MCP agents and servers with zero friction. It enables developers to spin up, aggregate, and route MCP servers through a single endpoint, providing a seamless way to create AI agents and integrate various tools.
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Quick Overview
Best for: Software & Gaming
What it does
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Best fit
Software & Gaming
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mcp-use
mcp-use is designed to simplify the deployment and management of MCP agents and servers by providing a unified gateway and SDKs for Python and JavaScript. It allows developers to spin up MCP servers, aggregate them through a single endpoint, and create AI agents with minimal setup. The platform supports hosted, ephemeral, on-premises, and third-party MCP servers, all managed through a centralized control plane. With built-in authentication, load balancing, metrics, and tracing, mcp-use offers production-grade observability and security from day one. It is ideal for developers and organizations looking to build AI-powered applications with flexible server management and integration capabilities.
Open source SDK and cloud infrastructure to help development teams quickly build and deploy custom AI agents with MCP servers, providing a unified control plane for managing MCP servers, configs, and access.
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Claim this listingKey Features
Single Endpoint Aggregation
Aggregate multiple MCP servers through a single endpoint for simplified access and management.
Open Source SDKs
Provides Python and JavaScript libraries to easily integrate and interact with MCP servers.
Managed MCP Gateway
Routes, authenticates, and load-balances MCP servers with built-in OAuth, ACLs, metrics, and tracing.
Flexible Server Deployment
Supports fully managed cloud servers, hosted short-lived servers, local VMs, and third-party MCP servers.
AI Agent Creation
Create AI agents with any model provider and tools using minimal code and zero setup time.
Production-grade Observability
Includes monitoring, metrics, cache, memory management, and tracing for robust server management.
Community Support
Active developer community for help, project sharing, and inspiration.
Pricing
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Use Cases
AI Agent Development
Build and deploy AI agents that interact with multiple MCP servers and tools seamlessly.
Server Aggregation and Routing
Aggregate and route requests to multiple MCP servers through a single managed gateway endpoint.
Managed and Self-hosted MCP Server Deployment
Deploy MCP servers in the cloud, on-premises, or proxy third-party servers with centralized control.
Integration with External Services
Connect MCP agents to external remote services and third-party MCP servers for extended functionality.
Integrations
Anthropic Claude
Integration with Anthropic's Claude model for AI agent interactions.
Google Drive
Supports integration with Google Drive as a tool for MCP agents.
Slack
Integration with Slack for communication and tool usage.
Third-party MCP Servers
Proxy and integrate third-party MCP servers behind the MCP gateway.
Benefits
Limitations
Frequently Asked Questions
What is mcp-use?
How do I create an AI agent with mcp-use?
Can I deploy MCP servers on-premises?
Does mcp-use provide authentication and security?
Getting Started
- 1 Install the mcp-use library via pip or npm.
- 2 Use the MCPClient class to connect to your MCP server pool.
- 3 Create an MCPAgent with your preferred model provider and tools.
- 4 Run queries through the agent to interact with MCP servers and tools.
Support
Community
Join the MCP community for help, project sharing, and inspiration.
Documentation
Open source libraries and usage examples available on GitHub.
API
Open source SDKs available on GitHub for Python and JavaScript with example usage.
Not specified in the available information.
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