Build and deploy MCP Apps and Servers
The mcp-use SDK is the fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents. Loved by developers.
Still writing code by hand?
Our open source tools are used by developers at top companies
Your fastest path to the ChatGPT Apps Store and Claude Connectors.
One codebase. Every surface where users and agents already work.
From first commit to production.
Every step of the MCP lifecycle. No extra tools.
Start from an SDK, a skill, or a vibe.
Scaffold with the mcp-use SDK. Install a skill into your coding agent. Or describe your app and watch it scaffold. Already writing MCP servers? Drop your existing code in unchanged.
- SDKScaffold a full MCP app in one command.
- SkillInstall the skill for your coding agent.
- VibePrompt-to-scaffold for first commits.
One push. Live in seconds.
Connect your repo once. Every push auto-deploys to Manufact Cloud. No YAML. No Dockerfile archaeology.
- GitHub AppConnect once. Every push auto-deploys to Manufact Cloud.
- Preview per branchA live URL for every pull request.
- Custom domainsShip your app under your own domain. SSL handled.
Derisk your path to the marketplaces.
Get your app in front of users in ChatGPT and Claude. Submission assets generated for you. Share an embedded chat anywhere you already have an audience.
- Marketplace checklistsChatGPT Apps Store and Claude Connectors requirements, ticked as you go.
- Submission assetsLogo, copy, and screenshots generated from your deploy.
- Embedded chatDrop a shareable chat onto your site, docs, or campaign page.
Preview it before a user sees it.
Cloud Inspector runs your MCP server against real clients. Fire tool calls, inspect JSON-RPC, swap models — no local setup.
- Cloud InspectorDebug from any browser.
- Model swapTest the same call against GPT, Claude, Gemini.
- Automatic evalsEval suites run across every model and client on every deploy.
Don't go blind in production.
See how people actually use your MCP app. Analytics, session replay, and observability built in — so you catch regressions before users report them.
- AnalyticsTraffic, tool-call volume, and latency at a glance.
- Session trackingReplay a user's conversation end-to-end.
- ObservabilityJSON-RPC traces, error rates, and alerts on regressions.
Build by hand. Or with Manufact.
Stitch together MCP server, React UI, hosting, auth, and scaling.
npx create-mcp-use-app scaffolds the whole stack.
Test by connecting to a live LLM and hoping.
Visual Inspector. Sandbox testing. No LLM required.
Manage your own deployment pipeline and branch previews.
git push auto-deploys via the GitHub App.
Build for ChatGPT or Claude or Gemini — separately.
Build once. Deploy to ChatGPT, Claude, and Gemini.
Developers love
Thousands of dev-teams are building with mcp-use
Been thinking about trying your @mcpuse today when I started building a ChatGPT app, but wasn't sure if it's the right use case. Now I assume it is 🙂
Great addition to the generic MCP Client collection.
Infra isn't just plumbing. It's distribution. Examples: AgentMail: inboxes for agents, mcp-use: MCP infra, DeepAware: RL for data center ops. Whoever owns the rails agents use to talk to the outside world ends up with Twilio-style power.
mcp-use is by far the best Python framework for building an agent MCP. It's so easy to set up an agent connected to MCP servers through the command line, that way I can quickly iterate on my MCP servers and test. Most people are using MCP servers in chat clients like Cursor / Claude Code, but MCP server use by agents will explode in the near future. I think it's important to test your server in an agent environment, and mcp-use provides that.
MCP-Use is the open source way to connect any LLM to any MCP server and build custom agents that have tool access, without using closed source or application clients.
that's why we love open-source! @NASA is building an agent with MCP using our library @mcpuse 🚀
Been thinking about trying your @mcpuse today when I started building a ChatGPT app, but wasn't sure if it's the right use case. Now I assume it is 🙂
Great addition to the generic MCP Client collection.
Infra isn't just plumbing. It's distribution. Examples: AgentMail: inboxes for agents, mcp-use: MCP infra, DeepAware: RL for data center ops. Whoever owns the rails agents use to talk to the outside world ends up with Twilio-style power.
mcp-use is by far the best Python framework for building an agent MCP. It's so easy to set up an agent connected to MCP servers through the command line, that way I can quickly iterate on my MCP servers and test. Most people are using MCP servers in chat clients like Cursor / Claude Code, but MCP server use by agents will explode in the near future. I think it's important to test your server in an agent environment, and mcp-use provides that.
MCP-Use is the open source way to connect any LLM to any MCP server and build custom agents that have tool access, without using closed source or application clients.
that's why we love open-source! @NASA is building an agent with MCP using our library @mcpuse 🚀
Awesome to see mcp-use support MCP-UI! We're aligning on the open spec with OAI and others to make sure the entire community benefits from complete compatibility
mcp-use is really into something good here.
mcp-use (@mcpuse) is building open-source dev tools and infrastructure for MCP to help dev teams quickly build and deploy custom AI agents with MCP servers.
awesome to see @mcpuse on product hunt today! for everyone needing to build with or around MCP! and yes, we'll do a small hack night with them next week to put that to the test as well 😉
MCP evals is here in @deepeval, metric name taken from @mcpuse 👀
🚀 @mcpuse launched! Open source infrastructure and dev tools for MCP agents: "Spin-up and aggregate MCP servers through a single endpoint and zero friction."
Awesome to see mcp-use support MCP-UI! We're aligning on the open spec with OAI and others to make sure the entire community benefits from complete compatibility
mcp-use is really into something good here.
mcp-use (@mcpuse) is building open-source dev tools and infrastructure for MCP to help dev teams quickly build and deploy custom AI agents with MCP servers.
awesome to see @mcpuse on product hunt today! for everyone needing to build with or around MCP! and yes, we'll do a small hack night with them next week to put that to the test as well 😉
MCP evals is here in @deepeval, metric name taken from @mcpuse 👀
🚀 @mcpuse launched! Open source infrastructure and dev tools for MCP agents: "Spin-up and aggregate MCP servers through a single endpoint and zero friction."
Really sharp execution, mcp-use nails the 'Vercel for MCP' play. Love how you've stripped deployment and aggregation down to a single endpoint with zero friction. Crypto infra teams, onchain data providers, and AI-powered DeFi dashboards could slot this in to speed up agent builds massively.
🦜🤖 MCP-Use Tools - Just launched: An open-source library that connects any LLM to MCP tools for custom agents, featuring seamless integration with LangChain and support for web browsing, Airbnb search, and 3D modeling capabilities.
<60s to deploy your ChatGPT App 🤯 With mcp-use creating your own app takes less than a minute. 1. npx create-mcp-use-app 2. Edit your react widgets 3. yarn deploy. Done! You can now connect your mcp server to ChatGPT and start chatting.
We implemented Code Mode in mcp-use's MCPClient . All you need to do is define which servers you want your agent to use, enable code mode, and you're done! The client will expose two tools: - One that allows the agent to progressively discover which servers and tools are available - One that allows the agent to execute code in an environment where the MCP servers are available as Python modules (SDKs)
Really sharp execution, mcp-use nails the 'Vercel for MCP' play. Love how you've stripped deployment and aggregation down to a single endpoint with zero friction. Crypto infra teams, onchain data providers, and AI-powered DeFi dashboards could slot this in to speed up agent builds massively.
🦜🤖 MCP-Use Tools - Just launched: An open-source library that connects any LLM to MCP tools for custom agents, featuring seamless integration with LangChain and support for web browsing, Airbnb search, and 3D modeling capabilities.
<60s to deploy your ChatGPT App 🤯 With mcp-use creating your own app takes less than a minute. 1. npx create-mcp-use-app 2. Edit your react widgets 3. yarn deploy. Done! You can now connect your mcp server to ChatGPT and start chatting.
We implemented Code Mode in mcp-use's MCPClient . All you need to do is define which servers you want your agent to use, enable code mode, and you're done! The client will expose two tools: - One that allows the agent to progressively discover which servers and tools are available - One that allows the agent to execute code in an environment where the MCP servers are available as Python modules (SDKs)
Built in the open.
One of the most adopted open-source MCP frameworks. Open from day one.
Begin your MCP journey
in the fastest way
Vibecode your MCP App
Describe what you want. Watch your MCP server and widgets scaffold in front of you.
From a template
Pick one of our templates and start from a known-good scaffold.
