Manufact
Managed MCP cloud to deploy, test, publish, and monitor MCP servers for ChatGPT, Claude, Cursor, and other AI clients.
Manufact earns its money when marketplace review is what's blocking you: publishing checks, the submission pack, and LLM-judged suites across ChatGPT and Claude attack weeks of blind resubmission — PredictLeads cites exactly that. Hobby at $25/mo (or $300 billed yearly, about 17% off) is a low-risk entry with $30 in credits. If you only need hosting, a self-hosted mcp-use on your own PaaS is legitimate. Watch the soft request caps: past your allowance, billing turns pay-as-you-go, so set a spend limit in Billing before a traffic spike.
Verified 20h ago · liveness 73/100 · cite: rightaichoice.com/tools/manufact
- Developers submitting an MCP server to the ChatGPT Apps Store or Claude Connectors
- Teams running MCP servers in production that need tool-call analytics and session debugging
- Startups that want one MCP build reaching ChatGPT, Claude, Cursor, Codex, and Copilot
- Engineers hosting an MCP server elsewhere who want cross-client evals and publish checks only
- Teams requiring on-premise, air-gapped, or self-hosted-only deployment of the managed cloud
- Low-code users who want a visual app builder instead of a repo, CLI, and SDK workflow
- Projects with flat, predictable traffic where usage-based credits add forecasting work
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Skip Manufact if you need on-prem or air-gapped deployment, or if you only want to host an MCP server with no interest in marketplace publishing checks and cross-client test suites.
Paid request allowances are soft caps: past Hobby's 300k requests/mo, billing continues pay-as-you-go, so set a spend limit in Billing before traffic spikes.
Free is a real trial (2 projects, 1 seat, 30k requests). Hobby at $25/mo, or $300/yr billed yearly, is cheap next to generic PaaS plus a separate test harness and compliance consultant. Enterprise is custom-quoted with volume credits, unlimited seats, and SOC 2 Type 2 / ISO 27001 — expect to justify it against building on self-hosted mcp-use.
In short
Manufact — Managed MCP cloud to deploy, test, publish, and monitor MCP servers for ChatGPT, Claude, Cursor, and other AI clients. Best for Developers submitting an MCP server to the ChatGPT Apps Store or Claude Connectors, Teams running MCP servers in production that need tool-call analytics and session debugging, Startups that want one MCP build reaching ChatGPT, Claude, Cursor, Codex, and Copilot. Free to start; paid plans from $25/mo.
What's new in Manufact
Checked todayAcross the latest 5 updates: 1 feature update and 4 news mentions.
Alpha Vantage automated MCP hosting and QA with Manufact
Alpha Vantage replaced a planned hand-built AWS MCP stack with Manufact for hosting, deployment, cross-client testing, and analytics.
OpenAI MCP Extensions: bring your app into ChatGPT as a Plugin
Guide to OpenAI MCP Extensions: open an MCP app from the ChatGPT sidebar, sync its UI with the conversation, and handle files in your own editor.
Test Your MCP Server in Claude Code, Codex, and ChatGPT
Manufact test suites now run MCP servers inside Claude Code, Codex CLI, and Pi alongside ChatGPT, Claude, and the Inspector, with an LLM judge scoring each run.
Agents That Answer with UI: CopilotKit × mcp-use
A CopilotKit agent returns an interactive map rendered by an MCP App built with the mcp-use SDK.
How to Distribute Your MCP Server Across ChatGPT, Claude, Muse, Grok, and Cursor
Compares public directory submissions for ChatGPT, Claude, Muse, and Cursor, plus custom MCP setup for Grok, and covers Inspector passes that fail in ChatGPT or Claude.
What people actually say about Manufact — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
60 mentions across 4 sources (Hacker News, YouTube, Bluesky, Lemmy) · researched Jul 6, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Fastest deployment path from GitHub to ChatGPT and Claude stores.
- +Cloud Inspector enables real-time debugging across multiple AI models.
- +Branch previews with unique URLs per PR streamline testing workflows.
- +Cross-client testing against ChatGPT, Claude, Gemini, and Copilot.
- +Free tier ($5 monthly credits) lowers entry barrier for solo developers.
- −Credit-based pricing can be confusing and potentially costly at scale.
- −No public case studies or independent reliability data available.
- −Tooling is tightly coupled to Manufact's ecosystem, making migration hard.
- −Advanced analytics and observability features may overwhelm beginners.
- −Limited community outside Hacker News launch threads.
- • Credit consumption varies per feature (requests, build minutes, evals, checklists) — easy to overshoot if not monitored
- • Branch previews and Cloud Inspector use credits too
Viability Score
How well maintained and how widely used is Manufact? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Deploy an MCP server from a GitHub repo, template, or CLI in under 60 seconds
- Auto-deploy every push via the mcp-use GitHub App
- Per-branch preview deployments at a unique URL
- Custom domains for deployed MCP endpoints
- Connect an externally hosted MCP server by URL for evals and publish checks
- Cross-client testing across ChatGPT, Claude, Grok, Meta Muse, Gemini Enterprise, Copilot 365
- Run one test scenario across GPT, Claude, and Gemini with LLM-judged pass/fail
- Run MCP test suites inside Claude Code, Codex CLI, and Pi
- Gate CI on test suites so a client regression blocks the merge
- Cloud Inspector to call tools, browse resources, preview widgets, replay JSON-RPC
- MCP server tunneling to expose a local server through a secure tunnel
- Publishing checks against ChatGPT Apps Store and Claude Connectors requirements
- Submission pack generates logo, copy, screenshots, reviewer test cases
- Analytics with tool-call volume, sessions, error rates, and p50/p95/p99 latency
- Embeddable public chat surface for your deployed MCP server
About Manufact
Manufact (formerly mcp-use) is a managed cloud for the full Model Context Protocol lifecycle. You deploy an MCP server from a Git repository, a deploy-ready template, or the CLI on the mcp-use SDK, and get a hosted endpoint with branch previews, custom domains, and GitHub App auto-deploy on every push. Its testing layer runs one scenario across GPT, Claude, and Gemini with LLM-judged pass/fail, and since October 2026 test suites also run inside Claude Code, Codex CLI, and Pi — results can gate CI so a client regression blocks a merge. Publishing is the other half: checks audit your app against ChatGPT Apps Store and Claude Connectors requirements, and a submission pack generates logo, copy, screenshots, and reviewer test cases. The Cloud Inspector lets you call tools, browse resources, preview widgets, and replay JSON-RPC from a browser, while analytics tracks tool-call volume, sessions, error rates, and p50/p95/p99 latency filtered by client and tool. You can also point it at an externally hosted MCP server by URL and buy only testing, publish checks, and analytics. Underneath sits the MIT-licensed mcp-use SDK for TypeScript and Python (10M+ downloads, 10k+ GitHub stars); the company is Y Combinator-backed.
Behind the Verdict
Manufact's advantage is that it owns both ends of the MCP problem. The open-source mcp-use SDK (TypeScript and Python, MIT, 10M+ downloads, 10k+ GitHub stars) is the same foundation the hosted platform deploys, so the path from scaffold to a live endpoint is short: `npx create-mcp-use-app`, `mcp-use login`, `mcp-use deploy`. Deployments cover any MCP framework, not just mcp-use — from GitHub, a template, or the CLI — with branch previews at a unique URL and custom domains. The testing layer is where depth shows. One scenario runs across GPT, Claude, and Gemini with an LLM judge scoring pass/fail per client, and since October 2026 those suites run inside Claude Code, Codex CLI, and Pi alongside ChatGPT, Claude, and the Inspector. Because results can gate CI, a client regression blocks the merge instead of surfacing after marketplace submission. The Cloud Inspector lets you call tools, browse resources, preview widgets, and replay JSON-RPC from any browser, and analytics filters tool-call volume, sessions, error rates, and p50/p95/p99 latency by client and tool. Publishing is the differentiator most hosting competitors skip: checks against ChatGPT Apps Store and Claude Connectors requirements, plus a submission pack that generates logo, copy, screenshots, and reviewer test cases. An embeddable public chat lets you test with real users before you submit. Weaknesses worth weighing. Analytics retention is tier-bound (7 days Free, 30 days Hobby, unlimited Enterprise), so deep historical investigations need Enterprise. Paid request allowances are soft caps — usage continues on pay-as-you-go past 300k requests on Hobby — and metered features consume your monthly credits, so budget forecasting matters. The Free tier is genuinely a trial: 2 projects, 1 seat, 30k requests with a hard stop. Teams needing on-prem or air-gapped deployment won't find it here, and low-code builders will bounce off the repo/CLI/SDK workflow. Enterprise adds SOC 2 Type 2, ISO 27001, and US/EU/APAC/Global regions, which regulated buyers should treat as a gate.
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Real-world workflow fit
Concrete scenarios for the personas Manufact actually fits — and what changes day-one when you adopt it.
Scaffold with `npx create-mcp-use-app --template mcp-apps`, deploy with `mcp-use deploy`, then run publishing checks and the submission pack against the ChatGPT Apps Store checklist.
Outcome: A hosted, branch-previewed endpoint and a complete listing kit in a day instead of weeks of blind resubmission.
Push to GitHub for auto-deploy, then watch tool-call volume, sessions, and p50/p95/p99 latency filtered by client and tool; replay failing JSON-RPC in the Cloud Inspector.
Outcome: Failing tool calls get traced to a specific client and tool without adding a separate observability stack.
Paste the external MCP URL into Manufact to run cross-client evals across GPT, Claude, and Gemini, plus publish checks and analytics, without migrating hosting.
Outcome: Cross-client regressions get caught before submission while the existing hosting stays put.
Use Cases
- Deploy an MCP server from a GitHub repo and get a hosted endpoint in minutes, with auto-deploy and branch previews on every push.
- Build and publish a ChatGPT App or Claude Connector from one mcp-use codebase and one deploy.
- Debug failing MCP tool calls across different models using the Cloud Inspector from any browser.
- Run the same test scenario across GPT, Claude, and Gemini and gate CI on the pass/fail results.
- Monitor production tool calls, sessions, latency, and error rates with per-client and per-tool filters.
- Embed a hosted public chat for your MCP server to test with real users before marketplace submission.
- Connect an MCP server hosted elsewhere by URL and use only the evals, publish checks, and analytics.
- Generate marketplace listing logo, copy, and screenshots with the submission pack.
Limitations
- Manufact Cloud is a hosting, testing, publishing, and observability platform for MCP servers and apps; it does not supply an underlying AI model of its own.
- The models exercised during cross-client testing belong to the connected clients (ChatGPT, Claude, Grok, Meta Muse, Gemini Enterprise, Copilot 365, Codex, Claude Code, Cursor), not to Manufact.
- The platform is aimed at developers shipping MCP products across AI marketplaces, so some familiarity with MCP servers and tooling is assumed.
as of 2026-10-18
Verification history
We have re-verified Manufact 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 10 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Manufact tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
A solo developer evaluating MCP hosting for a first server, or testing the publish checklist before committing budget.
What this tier adds
Free entry point: $5 monthly credits, 2 projects, 30k requests/mo with a hard stop, 1 seat, 7-day analytics retention.
Hobby
$25/mo (or $300 billed yearly)
Ideal for
A small team launching a ChatGPT App or Claude Connector to a marketplace and needing evals, publish checks, and preview deployments.
What this tier adds
Adds $30 credits then pay-as-you-go, 5 projects, 300k requests/mo soft cap, 3 seats, 30-day retention, public chat, end-to-end checks, submission pack, preview deployments, and scale-to-zero prevention.
Enterprise
Custom
Ideal for
An organization shipping MCP in production that needs compliance attestations, unlimited seats, and regional placement.
What this tier adds
Adds custom volume credits, unlimited projects and seats, unlimited analytics and log retention, US/EU/APAC/Global regions, SOC 2 Type 2 and ISO 27001, dedicated Slack support, and custom SLAs.
Where the pricing makes sense
The company stage and team size where Manufact's pricing actually pencils out — and where peers do it cheaper.
Free is a real trial (2 projects, 1 seat, 30k requests). Hobby at $25/mo, or $300/yr billed yearly, is cheap next to generic PaaS plus a separate test harness and compliance consultant. Enterprise is custom-quoted with volume credits, unlimited seats, and SOC 2 Type 2 / ISO 27001 — expect to justify it against building on self-hosted mcp-use.
Setup time & first value
How long it actually takes to get something useful out of Manufact — broken out by persona, not the marketing-page minute.
Solo developer: under an hour from `mcp-use login` to a live endpoint with the CLI. Platform team: about half a day to wire GitHub auto-deploy, domain, and CI-gated test suites. External-server users: minutes to connect by URL for evals and publish checks.
Switching to or from Manufact
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From self-hosted mcp-use: point the CLI at Manufact with `mcp-use deploy`, or install the mcp-use GitHub App for auto-deploy on push.
- →From a hand-built AWS MCP stack: deploy the existing server from its repo and add cross-client testing and analytics (the path Alpha Vantage took).
- →From raw MCP SDK transport: keep the server code, move transport, auth, and session handling to Manufact.
- ↗To self-hosted mcp-use: the SDK is MIT licensed — export the server and run it on your own PaaS, owning transport, auth, and sessions.
- ↗To a generic PaaS: redeploy the MCP server container and rebuild test harnesses and analytics separately.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Manufact”, and we withheld 6: 6 could not be judged, because “Manufact” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Manufact.
Official links
Tools that pair well with Manufact
Common stack mates teams adopt alongside Manufact, with the specific reason each pairing earns its keep.
Ida Pro Mcp
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Agentic Qe
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Featured Head-to-Head Comparisons
Manufact vs Spider Cloud
Choose Spider Cloud if you need fast, cost-effective web data extraction for RAG and AI agents. Pick Manufact if you are building MCP servers or ChatGPT/Claude apps and need managed cloud hosting with cross-client testing. They solve different problems and are not direct competitors.
Manufact vs Voyage Ai
Voyage AI and Manufact serve fundamentally different needs: voyage-ai excels at boosting retrieval accuracy in enterprise RAG with domain-specific embeddings and rerankers, while manufact is a cloud platform for building and deploying MCP servers and AI chat apps. Choose Voyage if you need high-quality, cost-efficient embeddings for specialized data (e.g., finance, legal) and can engage with enterprise sales. Choose Manufact if you're a developer shipping production MCP servers or ChatGPT/Claude apps and want fast deployment with cross-client testing, observability, and marketplace publishing.
Manufact vs Temporal Ai
If you need rock-solid durable execution for AI agents that must survive crashes and retries, Temporal AI is the battle-tested choice (used by OpenAI, Replit). If you're building MCP servers to ship ChatGPT/Claude apps quickly, Manufact provides a streamlined cloud platform with cross-client testing and marketplace publishing. They serve different needs—Temporal for workflow reliability, Manufact for MCP hosting.
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Ida Pro Mcp
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Godot Mcp Pro
Godot MCP Pro wires Claude and Cursor into the Godot 4 editor over WebSocket, with 187 AI tools for building, testing, and inspecting games
Agentic Qe
Agentic QE is an open-source MCP server that adds 60 QE agents and 76 skills to Claude Code, Cursor, Copilot and eight other coding agents.
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