Which MCP servers can actually deploy infrastructure, not just read it? Five compared

If you want an AI agent to deploy and run infrastructure through MCP, five hosted MCP servers can do real write work today: Vercel, Render, Railway, Netlify and Eyevinn Open Source Cloud (OSC). They differ in what the agent can create, whether it can tear things down again, and what is actually running underneath when it does.

Every row below comes from each platform's own MCP documentation, read on 6 November 2026. Tool lists change month to month, so treat the table as a dated snapshot.

What is the difference between an MCP server that reads and one that deploys?

A read-only server lets your agent look: list projects, fetch logs, search documentation. Most cloud MCP servers started there.

A deploying server lets the agent change things. It can create a database, ship your code to a public URL, set environment variables, restart a service and delete what it made. That needs more trust, so check which write actions a server exposes before you connect it to an agent that acts with your credentials.

Which hosting platforms have an MCP server that can deploy?

How should I read that table?

Vercel, Netlify and Render are at their best when what you deploy is a web app or a frontend with a managed database beside it. That is what those platforms are built around, and their MCP servers expose it well. Vercel's server added code deploys this summer, so older articles that call it read-only are out of date.

Render is explicit about its limits. Its MCP server does not support every configuration option at creation, and it leaves scaling changes and deletions to the dashboard and API. That is a defensible safety choice, and it is better to know it up front than to discover it mid-task.

Railway splits its tools in two. The hosted server is the default and the narrower one. The local server, run through the CLI, can create and remove services, volumes and domains, and Railway marks destructive actions so that clients ask before acting.

What does the OSC MCP server do that the others do not?

Two things, and both come from what OSC is rather than from the MCP layer.

The first is the catalog. OSC runs managed open-source services, and the MCP server can create any of them. When we checked today there were 198 published, from PostgreSQL and MinIO object storage to Keycloak for user logins and Uptime Kuma for monitoring, plus a long tail of media tools. Your agent is not limited to a web app and a database. If the project needs full-text search, a message queue or a video transcoder, it is the same create-service-instance call.

The second is what runs underneath. Every catalog service runs the unmodified upstream open-source container. A PostgreSQL instance on OSC speaks the PostgreSQL wire protocol, MinIO speaks S3 and Keycloak speaks OIDC, with no proprietary OSC API between your app and the service. If you leave, you run the same image on another cloud or your own servers and point your app at it. We wrote up that exit as a script in The Exit Test. This matters more when an agent makes the choices, because nobody stopped to read the exit terms.

The services your agent creates on OSC run in Stockholm, on Swedish-owned infrastructure.

Where OSC is the wrong pick: if your project is mostly a frontend and you want the preview-deploy-per-pull-request workflow, the platforms built around that workflow will fit better.

How do I connect the OSC MCP server to Claude Code?

You need an OSC account. The free Basic plan is enough to try it and asks for no card. Then run one command:

claude mcp add --transport http osc https://mcp.osaas.io/mcp 

Start Claude Code and type /mcp. A browser window opens, you sign in, pick the workspace the tools should act on and approve. The server implements OAuth 2.1 with PKCE, so there is no key to paste. Claude Desktop, Codex and ChatGPT use the same browser sign-in.

How do I connect it to Cursor?

Create a personal access token in the OSC console under Settings, API, and add this to .cursor/mcp.json:

{ "mcpServers": { "osc": { "type": "http", "url": "https://mcp.osaas.io/mcp", "headers": { "Authorization": "Bearer <personal-access-token>" } } } } 

Keep that file out of git, since the token acts as you.

What can an agent actually do once it is connected?

Three prompts that work, and the tools the agent picks for them:

Create a Postgres database called appdb and give me the internal connection string.

This is create-database with type: postgres. Credentials are generated for you, and the database is internal-only by default, so apps in the same workspace reach it over internal DNS without exposing it to the internet.

Deploy github.com/me/my-api as an app and connect it to appdb.

create-my-app builds the repository (Node.js, Python, Go, .NET, PHP or WebAssembly) and gives it a stable HTTPS URL, and wait-for-app-ready reports when it is live. The app has to listen on port 8080.

Back up appdb, then show me everything I have running.

That is create-backup and list-my-services. The agent sees your own workspace, not a generic catalog, so it can manage what already exists.

Deleting is deliberately slower. delete-service-instance first returns a confirmation token and acts only on a second, confirmed call, so an agent that mistakes "stop" for "delete" does not remove a database on the first try.

Can I use my existing Claude subscription instead of buying platform credits?

Yes. The MCP server is a connector, so the AI runs on whatever Claude, ChatGPT or Cursor plan you already pay for. OSC tokens pay for running services, not for prompts, and you are never billed per prompt or for an AI mistake.

What does OSC cost?

Basic is free, with 100 tokens granted once and no card. Personal is 15 EUR a month excluding VAT and adds 40 tokens a day. A single running service typically uses 10 to 100 tokens a day, so size the plan against what you keep running rather than what you try once. Paid plans bill from day one, there is no trial on any plan, and you can cancel any time. Custom domains start at the Professional plan.

Which one should I pick?

Pick by the job, not by the protocol. If the agent's job is to ship a frontend, use the platform you would have picked without MCP. If the job is to assemble a backend out of open-source pieces and keep the option to take every one of them with you, try OSC: create a free account, run the one command above and ask your agent for a database.

Setup for VS Code, Windsurf, Codex and ChatGPT is on the OSC MCP page. A longer walkthrough: The MCP server that provisions a full backend your AI agent can deploy, and you can walk away.

If a platform's tools have changed since 6 November 2026, tell us in the comments and we will update the table.