Cookie preferences

We use cookies to improve your experience. See our Privacy Policy.

Manufact

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.

Your fastest path to the ChatGPT Apps Store and Claude Connectors.

One codebase. Every surface where users and agents already work.

AI Chats
ChatGPTClaudeGemini EnterpriseCopilot 365CopilotKit
Coding agents
CodexClaude CodeCursorVS Code
Internal agents
OpenAI AgentsClaude Agent SDKMastraLangchainVercel AI SDK
ChatGPT Apps Store and Claude Connectors

From first commit to production.

Every step of the MCP lifecycle. No extra tools.

build

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.

deploy

One push. Live in seconds.

Connect your repo once. Every push auto-deploys to Manufact Cloud. No YAML. No Dockerfile archaeology.

  • GitHub App
    Connect once. Every push auto-deploys to Manufact Cloud.
  • Preview per branch
    A live, unique URL for every pull request
  • Custom domains
    Ship your app under your own domain. SSL handled.
publish

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 checklists
    Know when you're ready to submit
  • Submission assets
    Logo, copy, and screenshots generated for you
  • Embedded chat
    Automatic sharable chat for your mcp server
    mcp.acme.com/chat
iterate

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.

monitor

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.

  • Analytics
    Traffic, tool-call volume, and latency at a glance.
  • Session tracking
    Replay a user's conversation end-to-end.
  • Observability
    Traces, error rates, and alerts on regressions.

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 🙂

Paolo Perazzo
Paolo Perazzo@SiVola

Great addition to the generic MCP Client collection.

Kingsley Uyi Idehen
Kingsley Uyi Idehen@kidehen

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.

Vedika Jain
Vedika Jain@vedikaja_in

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.

Matt Wang
Matt Wang@mcpjams

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.

Adam Silverman
Adam Silverman@adamsilverman

that's why we love open-source! @NASA is building an agent with MCP using our library @mcpuse 🚀

pederzh
pederzh@pederzh

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 🙂

Paolo Perazzo
Paolo Perazzo@SiVola

Great addition to the generic MCP Client collection.

Kingsley Uyi Idehen
Kingsley Uyi Idehen@kidehen

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.

Vedika Jain
Vedika Jain@vedikaja_in

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.

Matt Wang
Matt Wang@mcpjams

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.

Adam Silverman
Adam Silverman@adamsilverman

that's why we love open-source! @NASA is building an agent with MCP using our library @mcpuse 🚀

pederzh
pederzh@pederzh

Built in the open.

One of the most adopted open-source MCP frameworks. Open from day one.

9M+

SDK downloads across Python and TypeScript.

10k+

GitHub stars. Open-source since day one.

<60s

From git push to live MCP App or Server.

Our open source tools are used by developers at top companies

6sense logo
Elastic logo
IBM logo
Innovacer logo
Intuit logo
NVIDIA logo
Oracle logo
Red Hat logo
Tavily logo
Verizon logo
6sense logo
Elastic logo
IBM logo
Innovacer logo
Intuit logo
NVIDIA logo
Oracle logo
Red Hat logo
Tavily logo
Verizon logo

Frequently asked questions

Everything you need to build, deploy, test, and publish with Manufact.

What is Manufact?

Manufact (formerly mcp-use) is a platform for deploying, testing, observing, and publishing MCP servers and MCP apps. It's built by the team behind the open-source mcp-use SDKs for TypeScript and Python and the open-source MCP Inspector. Deploys run from GitHub, the CLI, or Manufact's own MCP server, and the platform covers the lifecycle after deploy: cross-client testing, MCP-native analytics, and publishing checks for the ChatGPT Apps Store and Claude Cloud Connectors.

How fast can I deploy an MCP server on Manufact?

Under 60 seconds from git push to a live MCP endpoint. Connect the GitHub App once and every push deploys automatically, or use npx mcp-use deploy from the CLI. An agent can also drive deployments through Manufact's official MCP server.

Which languages and frameworks does Manufact support?

TypeScript and Python are first-class through the mcp-use SDKs, with presets for FastMCP and other frameworks, plus a Dockerfile option for anything else. You can also connect an MCP server hosted elsewhere by URL and use testing, analytics, and publish checks without moving your hosting.

How do I test an MCP server across different AI clients?

Manufact test suites exercise your deployed server's tools across clients and swap models between GPT, Claude, and Gemini, with LLM-judged pass/fail results per client and model. Suites can gate CI, so a regression in any client blocks the merge. The embedded Cloud Inspector also lets you invoke tools, browse resources, and preview widgets against real clients with no local setup.

What is the MCP Inspector?

MCP Inspector is an open-source tool maintained by Manufact for debugging MCP servers: tool testing, resource browsing, prompt testing, real-time JSON-RPC logging, and widget preview with full window.openai emulation. Run it hosted at inspector.manufact.com, locally with npx @mcp-use/inspector, or self-hosted via Docker. Inside the Manufact dashboard, the Cloud Inspector runs against your deployed server directly.

What analytics do I get for my MCP server?

Tool calls, sessions, error rates with issue triage, and p50/p95/p99 latency per tool, resource, and prompt. Traffic breaks down by client (ChatGPT, Claude, Cursor, Windsurf, custom), client version, protocol version, and country. Session replay shows the full timeline of each session, and an internal-traffic toggle excludes dashboard and inspector calls from production numbers.

How does authentication work for MCP servers on Manufact?

OAuth ships with six documented providers: Auth0, Better Auth, Clerk, Keycloak, Supabase, and WorkOS, plus support for any custom provider that supports dynamic client registration. Your tools receive verified user context on every call. Clients connect with OAuth 2.1 with PKCE or bearer tokens.

How do I publish an MCP app to the ChatGPT Apps Store or Claude Connectors?

Manufact runs six categories of publishing checks mapped to store requirements: protocol and discovery, tool conformance, security and policy, metadata and configuration, domain/TLS/CSP, and assets. Each failed check comes with fix guidance and an autofix flow. E2E checks then run your server live inside ChatGPT and Claude to verify tool calls and widget rendering, and a generated submission pack produces listing copy, tool justifications, and reviewer test cases.

Do pull requests get preview deployments?

Yes. Every branch gets its own MCP URL (<slug>--br-<branch>.run.mcp-use.com/mcp), so reviewers can point a real client at the change before merge. Available on Hobby and above.

Is mcp-use open source?

Yes. The mcp-use SDKs for TypeScript and Python (servers, clients, and agents) and the MCP Inspector are open source, with 7M+ downloads and 10k+ GitHub stars. The Manufact cloud platform builds on them.

How much does Manufact cost?

The Free plan is $0 and includes $5/month in usage credits. Hobby is $25/month and adds preview deployments, E2E checks, and the submission pack. Startup is $250/month with all regions, and Enterprise is custom. Usage is metered ($0.10 per 1k tool-call requests, $1 per eval run, $2 per E2E check); discovery traffic like tools/list is never billed.

Can I use Manufact without hosting my server there?

Yes. Connect an existing remote MCP server by URL and get the Chat interface, test suites, publish checks, and the submission pack against it. Hosting on Manufact adds deploys from GitHub, preview environments, and gateway-level analytics.

Begin your MCP journey
in the
fastest way

From a Git repository

Already have an MCP server on GitHub? Deploy it with one click.

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.