广告合作
MCP.so
登录

Build and Deploy a remote MCP server to Cloud Run in 5 minutes

@jackwotherspoon

代码仓库

基本信息

分类

开发工具

许可证

Apache-2.0 license

传输方式

stdio

作者

jackwotherspoon

关于 Build and Deploy a remote MCP server to Cloud Run in 5 minutes

Deploy and host a remote MCP server on Cloud Run

#mcp#cloud-run#remote-mcp-server

Build and Deploy a remote MCP server to Cloud Run in 5 minutes 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-on-cloudrun": {
      "command": "uv",
      "args": [
        "run",
        "test_server.py"
      ]
    }
  }
}

Build and Deploy a remote MCP server to Cloud Run in 5 minutes 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is ☁️ 🚀 Build and Deploy a remote MCP server to Cloud Run in 5 minutes?

This project provides a quick-start template and guide to build a remote MCP server using FastMCP and deploy it to Google Cloud Run. It demonstrates how to run a Model Context Protocol server over the streamable-http (or sse) transport, making it centrally accessible, scalable, and secured with authentication. It is aimed at developers who want to move from local MCP servers to a remote, shareable infrastructure.

How to use ☁️ 🚀 Build and Deploy a remote MCP server to Cloud Run in 5 minutes?

Clone the repository, set your Google Cloud project, and deploy the server with gcloud run deploy mcp-server --no-allow-unauthenticated --region=us-central1 --source .. After deployment, run gcloud run services proxy mcp-server --region=us-central1 to create an authenticated local tunnel. Test the connection using uv run test_server.py, which exercises the add and subtract tools.

Key features of ☁️ 🚀 Build and Deploy a remote MCP server to Cloud Run in 5 minutes

  • Deploys a remote MCP server on Cloud Run with automatic scaling.
  • Enforces authentication via the --no-allow-unauthenticated flag and IAM roles.
  • Uses FastMCP for a fast, Pythonic server implementation.
  • Supports streamable-http transport (default) with sse as an option.
  • Includes two example math tools: add and subtract.
  • Provides a local proxy tunnel for secure client connections.

Use cases of ☁️ 🚀 Build and Deploy a remote MCP server to Cloud Run in 5 minutes

  • Share a centralized MCP server across a team so everyone uses the same tools.
  • Run an MCP server remotely to eliminate local setup and maintenance for each developer.
  • Leverage Cloud Run’s scalability to handle variable request loads from AI assistants.
  • Secure an MCP server with authenticated requests to prevent public access.

常见问题

1

What transports does this MCP server support?

It uses `streamable-http` by default, but you can switch to `sse` by changing the transport parameter in `server.py` to `transport="sse"`.

2

How do I deploy the MCP server to Cloud Run?

You can deploy from source with `gcloud run deploy mcp-server --no-allow-unauthenticated --region=us-central1 --source .` or from a container image built via Cloud Build. Both options require the `--no-allow-unauthenticated` flag.

3

How do I authenticate MCP clients?

Use the Cloud Run proxy by running `gcloud run services proxy mcp-server --region=us-central1`. This creates an authenticated tunnel to your service. You must also ensure that the caller (or the proxy) has the `roles/run.invoker` IAM role.

4

What are the prerequisites to get started?

You need Python 3.10+ (required by FastMCP), the Google Cloud SDK (`gcloud`), and Git for cloning the repository.

5

What tools are included in the example server?

The example Math MCP server provides two tools: `add` (returns the sum of two numbers) and `subtract` (returns the difference).

评论

开发工具 分类下的更多 MCP 服务器

Nebelus

Nebelus

Nebelus is an enterprise agentic-AI platform for regulated industries. This MCP server exposes the Nebelus Construction API: ~48 tools that give an MCP client full agent build parity — create/update/probe agents, edit ag

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

1

Meticulous

Meticulous

Eddyter AI Rich Text Editor MCP

EddyterAI

Set up and manage the Eddyter AI rich text editor by talking to your AI agent — for Claude, Cursor, Codex and other MCP tools. A Model Context Protocol server that lets AI tools add Eddyter to a React, Next.js, Vite or R

9

LocalCan

LocalCan

Gives AI agents public URLs (tunnels) for localhost, live HTTP traffic inspection, snapshot publishing, and access control. Part of LocalCan, the ngrok alternative for Mac, Windows and Linux. Free plan.

82
广告合作