P
pomerium/mcp-app-demo
Demo of securing MCP servers and clients with Pomerium
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
客户端配置（取自该仓库的安装命令）
{
"mcpServers": {
"pomerium-mcp-app-demo": {
"command": "npx",
"args": ["shadcn@latest"]
}
}
}解析自我们于 2026-11-07 抓取的该仓库 README；我们未执行过。
command/args 来自仓库写明的安装命令；不确定时请以该项目 README 为准。
VS Code（.vscode/mcp.json —— 键名是 servers）
{
"servers": {
"pomerium-mcp-app-demo": {
"command": "npx",
"args": ["shadcn@latest"]
}
}
}VS Code 顶层键是 <code>servers</code>，其余与上面那份相同。
Claude Code（命令行）
claude mcp add --transport stdio pomerium-mcp-app-demo -- npx shadcn@latest
Claude Code 不收 JSON 文件，用这条命令直接加。
配置项的键名以你的客户端为准：客户端与 CLI
- 来源明细
- 收录自 abordage/awesome-mcp 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
- 安装
npx shadcn@latest
常见问题（答案都来自我们的记录）
怎么安装？
该仓库给出的安装命令是
npx shadcn@latest。我们的记录里它是仓库自己提供的；不保证在你的客户端上直接可用。它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
我们收录于 2026-11-05；最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
Welcome to the Pomerium Chat, a minimal chat application for showcasing remote M
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
https://github.com/user-attachments/assets/50a17106-a471-4f64-be81-982c09d4689e
## Pre-requisites
1. Linux or MacOS host
2. Docker and Docker Compose
3. Your machine should have port 443 exposed to the internet so that it could acquire TLS certificates from LetsEncrypt and OpenAI could call your MCP server endpoints.
4. OpenAI API Key
## Quickstart
### Environment Variables
Create a .env-mcp-app-demo file in the root directory and add the following environment variables:
bash
OPENAI_API_KEY=your_api_key_here
### Pomerium Config
Update pomerium-config.yaml and replace YOUR-DOMAIN with the subdomain you control. Create A DNS records for relevant hosts (or .YOUR-DOMAIN).
By default, the access policy limits access to users with emails in YOUR-DOMAIN. See policy language reference if you need to adjust it.
### Docker Compose
See docker-compose.yaml file in this repo.
bash
docker compose up -d
It includes a demo SQLite server that requires a demo database, for example https://github.com/jpwhite3/northwind-SQLite3 that needs be saved as sqlite.db.
### Testing
Now you should be able to navigate to https://mcp-app-demo.YOUR-DOMAIN/.
A sign-in page would open. After you signed in, you should be redirected to the application itself.
There should be a demo database server (Database) acessible and in Connected status. Click on it to use it in the conversation.
Now you may ask some questions like "What were our sales by year", and see how OpenAI large language model inference would interact with the MCP database server running on your computer to obtain the answers.
# How does it work
See Model Context Protocol Capability Overview for more details.
## Token Vocabulary
External Token (TE):
An externally-facing token issued by Pomerium that represents the user's session. This token is used by external clients (such as Claude.ai, OpenAI, or your own apps) to authenticate requests to Pomerium-protected MCP servers.
Example: The token you provide to an LLM API or agentic framework to allow it to call your MCP server.
Internal Token (TI):
An internal authentication token that Pomerium obtains from an upstream OAuth2 provider (such as Notion, Google Drive, GitHub, etc.) on behalf of the user. This token is never exposed to external clients. Pomerium uses this token to authenticate requests to the upstream service when proxying requests to your MCP server.
Pomerium acts as a secure gateway between Model Context Protocol (MCP) clients and servers. It provides authentication and authorization for local HTTP MCP servers, using OAuth 2.1 flows. This setup is especially useful when your MCP server needs to access upstream APIs that require OAuth tokens (such as Notion, Google Drive, GitHub, etc.).
It also enables you to build internal applications that use agentic frameworks or LLM APIs capable of invoking MCP servers, as demonstrated in this repository.
To understand this setup, let's look at how an MCP client communicates with MCP servers that are protected by Pomerium.
## 1. Exposing an Internal MCP Server to a Remote Client
https://github.com/user-attachments/assets/c7a809ad-6f0a-4ea3-94a2-6cf22ea6d27b
Suppose you want to allow an external MCP client (like Claude.ai) to access your internal MCP server, but you want to keep it secure. Pomerium sits in front of your server and manages authentication and authorization for all incoming requests.
## Pre-requisites
1. Linux or MacOS host
2. Docker and Docker Compose
3. Your machine should have port 443 exposed to the internet so that it could acquire TLS certificates from LetsEncrypt and OpenAI could call your MCP server endpoints.
4. OpenAI API Key
## Quickstart
### Environment Variables
Create a .env-mcp-app-demo file in the root directory and add the following environment variables:
bash
OPENAI_API_KEY=your_api_key_here
### Pomerium Config
Update pomerium-config.yaml and replace YOUR-DOMAIN with the subdomain you control. Create A DNS records for relevant hosts (or .YOUR-DOMAIN).
By default, the access policy limits access to users with emails in YOUR-DOMAIN. See policy language reference if you need to adjust it.
### Docker Compose
See docker-compose.yaml file in this repo.
bash
docker compose up -d
It includes a demo SQLite server that requires a demo database, for example https://github.com/jpwhite3/northwind-SQLite3 that needs be saved as sqlite.db.
### Testing
Now you should be able to navigate to https://mcp-app-demo.YOUR-DOMAIN/.
A sign-in page would open. After you signed in, you should be redirected to the application itself.
There should be a demo database server (Database) acessible and in Connected status. Click on it to use it in the conversation.
Now you may ask some questions like "What were our sales by year", and see how OpenAI large language model inference would interact with the MCP database server running on your computer to obtain the answers.
# How does it work
See Model Context Protocol Capability Overview for more details.
## Token Vocabulary
External Token (TE):
An externally-facing token issued by Pomerium that represents the user's session. This token is used by external clients (such as Claude.ai, OpenAI, or your own apps) to authenticate requests to Pomerium-protected MCP servers.
Example: The token you provide to an LLM API or agentic framework to allow it to call your MCP server.
Internal Token (TI):
An internal authentication token that Pomerium obtains from an upstream OAuth2 provider (such as Notion, Google Drive, GitHub, etc.) on behalf of the user. This token is never exposed to external clients. Pomerium uses this token to authenticate requests to the upstream service when proxying requests to your MCP server.
Pomerium acts as a secure gateway between Model Context Protocol (MCP) clients and servers. It provides authentication and authorization for local HTTP MCP servers, using OAuth 2.1 flows. This setup is especially useful when your MCP server needs to access upstream APIs that require OAuth tokens (such as Notion, Google Drive, GitHub, etc.).
It also enables you to build internal applications that use agentic frameworks or LLM APIs capable of invoking MCP servers, as demonstrated in this repository.
To understand this setup, let's look at how an MCP client communicates with MCP servers that are protected by Pomerium.
## 1. Exposing an Internal MCP Server to a Remote Client
https://github.com/user-attachments/assets/c7a809ad-6f0a-4ea3-94a2-6cf22ea6d27b
Suppose you want to allow an external MCP client (like Claude.ai) to access your internal MCP server, but you want to keep it secure. Pomerium sits in front of your server and manages authentication and authorization for all incoming requests.
收录徽章（可选）
想把收录标记放进 README 就复制这行，可选，不影响收录。
[](https://anclum.com/zh/s/pomerium-mcp-app-demo/)
- 来源
- awesome · https://github.com/pomerium/mcp-app-demo
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- MCP 服务
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