Build
Connect & operate
Design & teams
Start hereScope a build in one callBring a spec, a wireframe, or a paragraph. You leave with an architecture, a timeline, and a number.Book a scoping call
AI software
LLM & data systems
Vibe coding
Ready to ship?Put AI where the work isAgents, RAG, and private LLMs wired into the systems your team already uses — not a chatbot bolted to a homepage.Discuss an AI project
Domain firstWe learn your workflow before we model itRegulated, operational, or high-volume — the constraints belong in the schema, not in a training doc.Talk about your domain
Plan smarterEstimate before you commitCost ranges, scope templates, and the questions we ask in discovery — free, no form.Open the cost calculator
Real conversationsTalk with a technical leadNo SDR, no discovery gauntlet. The person on the call is the one who scopes the build.Book a call
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

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

Related on DEV.co

Explore the category and the services that help you build with it.

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.

Build it with a software development company

DEV.co is a software development company delivering production systems to teams building on open source. Our engineers design, integrate, and ship across web, APIs, AI, data, and cloud. If mcp-use is part of your mcp servers roadmap, we 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.