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MCP Servers · mcp-use

mcp-use

mcp-use is a full-stack TypeScript/Python framework for building MCP (Model Context Protocol) servers and interactive apps that integrate with Claude, ChatGPT, and other AI agents. It includes an SDK for development, an in-browser inspector for testing, and optional cloud deployment through Manufact MCP Cloud.

Source: GitHub — github.com/mcp-use/mcp-use
10.3k
GitHub stars
1.4k
Forks
TypeScript
Primary language
MIT
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositorymcp-use/mcp-use
Ownermcp-use
Primary languageTypeScript
LicenseMIT — OSI-approved
Stars10.3k
Forks1.4k
Open issues131
Latest release[email protected] (2026-07-06)
Last updated2026-07-08
Sourcehttps://github.com/mcp-use/mcp-use

What mcp-use is

mcp-use provides a strongly-typed SDK (TypeScript/Python) for MCP server and app development, featuring tool/resource definition with Zod schema validation, React widget support for cross-client UIs, auto-discovery of components, and built-in introspection endpoints. The framework abstracts MCP protocol details while exposing low-level configuration.

Quickstart

Get the mcp-use source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/mcp-use/mcp-use.gitcd mcp-use# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Rapid MCP Server Development

Build production-ready MCP servers in minutes with declarative tool definitions, schema validation, and built-in inspector for local debugging before deployment.

Interactive AI Agent Widgets

Create React-based UI components that render consistently across Claude, ChatGPT, and other MCP clients without platform-specific rewrites.

Multi-LLM Integration Testing

Use the online/OSS MCP Inspector to validate server behavior and protocol compliance before connecting to production Claude or ChatGPT instances.

Implementation considerations

  • Requires Node.js 18+ (TypeScript) or Python 3.8+ (Python); ensure runtime compatibility in your deployment environment.
  • Widget components must be React-based and colocated in `resources/` directory; non-React or remote component architectures require workarounds.
  • Schema validation via Zod adds runtime overhead; review Zod performance for high-throughput tool definitions.
  • Inspector is hosted at `http://localhost:3000/inspector` by default; network/firewall configuration needed for remote debugging.
  • Latest version (1.34.2, 2026-07-06) released recently with active development; monitor breaking changes in minor releases.

When to avoid it — and what to weigh

  • Non-AI Agent Integrations — mcp-use is MCP-specific; unsuitable for traditional REST API development or non-LLM system integrations.
  • Complex Stateful Services — The framework is optimized for request/response tool calls; applications requiring heavy stateful management or WebSocket persistence may require extensive custom scaffolding.
  • Strict Language Lock-In — If your team relies exclusively on languages outside TypeScript/Python, or cannot adopt Node.js/Python runtimes, this framework is not a fit.
  • Proprietary Deployment Requirements — The cloud deployment option (Manufact MCP Cloud) is external; if you need full on-premise control without third-party infrastructure, evaluate self-hosting complexity.

License & commercial use

MIT License (permissive OSI-approved). Allows commercial use, modification, and distribution with no copyleft obligations. Attribution recommended but not required.

MIT License permits unrestricted commercial use, including building for-profit MCP apps and servers. No licensing restrictions on apps built with mcp-use. Verify any third-party dependencies (e.g., Zod, React) for their own commercial terms. Manufact MCP Cloud is a separate commercial service; cloud deployment is optional.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationStrong
License clarityClear
Deployment complexityModerate
DEV.co fitStrong
Assessment confidenceHigh
Security considerations

MCP servers expose tool endpoints; validate and sanitize all inputs via Zod schemas (framework assists but developer-responsible). Inspector endpoint (`/inspector`) runs on localhost by default—ensure network isolation in development. Widget rendering in MCP clients depends on client's XSS/content security policies; malicious props could leak data if widgets are not properly sandboxed. Review dependency supply chain (Zod, React, Node/Python stdlib). No explicit mention of OWASP practices, rate-limiting, or auth mechanisms in framework; implement at application level.

Alternatives to consider

Claude SDK (Anthropic)

Direct Python/JavaScript library for Claude API; simpler for single-LLM integrations but lacks MCP-agnostic abstraction and widget support.

LangChain / LlamaIndex

Broader LLM orchestration frameworks with multi-model support; heavier footprint and steeper learning curve, but more flexible for non-MCP workflows.

Pydantic AI (Anthropic/community)

Python-first framework for agent development with structured outputs; less MCP-focused and fewer visualization/widget primitives than mcp-use.

Software development agency

Build on mcp-use with DEV.co software developers

Start with mcp-use in minutes. Use the TypeScript or Python SDK to define tools, create interactive widgets, and deploy to production—or evaluate Manufact MCP Cloud for managed hosting.

Talk to DEV.co

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mcp-use FAQ

Can I use mcp-use for ChatGPT and Claude simultaneously?
Yes. Widgets and tools are designed as platform-agnostic MCP implementations. A single server/app will work with both clients if they support MCP protocol and widget rendering.
What happens if a client doesn't support widgets?
The framework falls back to the `message` field (plain text). Define both rich widget responses and text fallbacks for compatibility.
Do I have to use Manufact MCP Cloud for deployment?
No. Cloud deployment is optional. Self-host by running the Node.js/Python server on any infrastructure (VPS, Docker, Kubernetes, etc.). Cloud adds convenience for CI/CD and observability.
Is commercial support available?
Not clearly stated in provided data. Check mcp-use.com or Discord community for support options. Manufact may offer commercial support separately.

Software development & web development with DEV.co

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If mcp-use is part of your mcp servers roadmap, our team can implement, customize, migrate, and maintain it.

Ready to Build AI-Powered MCP Apps?

Start with mcp-use in minutes. Use the TypeScript or Python SDK to define tools, create interactive widgets, and deploy to production—or evaluate Manufact MCP Cloud for managed hosting.