learning-mcp-server

learning-mcp-server

A minimal MCP server with three toy tools (add, echo, current_time) for learning deployment on SAP BTP Cloud Foundry.

Category
访问服务器

README

learning-mcp-server

A minimal MCP server (three toy tools: add, echo, current_time) meant purely for learning how MCP servers deploy and run on SAP BTP's Cloud Foundry trial environment. No auth, no SAP backend calls — just get something running end to end.

Step 1 — Get a trial account

  1. Go to https://www.sap.com/products/technology-platform/trial.html and sign up (SAP account required; free, no time-limited data beyond the 90-day trial window).
  2. After signup you land in the SAP BTP cockpit with a subaccount and a Cloud Foundry space already created for you.

Keep in mind while you're learning: the trial account is for personal, non-production exploration only, resets after 90 days (or 30 days of inactivity), and has no SLA. That's all fine for this purpose.

Step 2 — Enable Cloud Foundry environment

  1. In the cockpit, open your subaccountCloud Foundry Environment.
  2. If it's not already enabled, click Enable Cloud Foundry, choose the free/trial plan, keep defaults, and create it.
  3. Note the API Endpoint shown here (something like https://api.cf.us10-001.hana.ondemand.com) — you'll need it to log in.
  4. A default space (usually called dev) is created automatically.

Step 3 — Install the Cloud Foundry CLI

Install cf from https://github.com/cloudfoundry/cli#installers-and-compressed-binaries (or via your package manager, e.g. brew install cloudfoundry/tap/cf-cli on macOS).

Verify:

cf --version

Step 4 — Log in

Trial accounts authenticate via SSO passcode rather than username/password:

cf login -a <API-ENDPOINT-FROM-STEP-2> --sso

This prints a URL — open it in your browser, copy the one-time passcode shown there, and paste it back into the terminal prompt. Then select your org and the dev space when prompted (or run cf target -o <your-org> -s dev afterward).

Step 5 — Deploy the server

From this project folder:

cf push

cf push reads manifest.yml, uploads the code, builds it with the Python buildpack, and starts it. When it finishes, it prints a route — something like:

routes: learning-mcp-server-<random>.cfapps.us10-001.hana.ondemand.com

That's your server's public HTTPS URL. Your MCP endpoint is at <that-url>/mcp.

Important for learning purposes only: this deployment has no authentication — anyone with the URL could call it. That's acceptable for a throwaway trial-account experiment, but never deploy an unauthenticated server like this with real data or real SAP system access behind it.

Step 6 — Test it

The easiest way to poke at it directly is the official MCP Inspector:

npx @modelcontextprotocol/inspector

This opens a local web UI. Choose Streamable HTTP as the transport, paste in https://<your-route>/mcp, connect, and you should see the three tools (add, echo, current_time) listed — click one to try it.

Step 7 — Connect it to Claude Desktop (optional)

Claude Desktop's config expects a local command, but remote Streamable HTTP servers can be bridged in via mcp-remote:

{
  "mcpServers": {
    "learning-server": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://<your-route>/mcp"]
    }
  }
}

Restart Claude Desktop and ask it to add two numbers or echo some text.

Useful commands while learning

cf logs learning-mcp-server --recent   # see recent logs (crash cause etc.)
cf logs learning-mcp-server            # tail live logs
cf apps                                 # list deployed apps and their routes/state
cf restart learning-mcp-server          # restart after config changes
cf delete learning-mcp-server           # tear it down, free up memory quota

Where to go from here

Once this deploys and responds correctly:

  1. Add a tool that calls a real SAP API (e.g. a public S/4HANA sandbox OData service, no auth needed to start).
  2. Then introduce a BTP Destination instead of a hardcoded URL.
  3. Then add authentication (SAP Cloud Identity Services / XSUAA) in front of the server, following the security pattern from the earlier architecture discussion.

Each of those is a small, isolated next step — happy to scaffold any of them when you're ready.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选
mcp-server-qdrant

mcp-server-qdrant

这个仓库展示了如何为向量搜索引擎 Qdrant 创建一个 MCP (Managed Control Plane) 服务器的示例。

官方
精选
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选