# Install Page Systems in an OpenAI Agents SDK agent

Connect the agent to the Page Systems MCP server. Its tools then appear to the model next to your own: list the page types, read a schema, create a page, read the answer.

Tested with `openai-agents` 0.23.1 (Python) and `@openai/agents` 0.20.0 (TypeScript).

## 1. Set your API key

Create a key in the [dashboard](https://app.pagesystems.ai/dashboard/keys) (it starts with `ap_live_` and is shown once) and set it where your agent runs. Never commit it.

```bash
export PAGE_SYSTEMS_API_KEY=ap_live_...
```

## 2. Python

```bash
pip install openai-agents
```

```python
import os
import urllib.request

from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

# The Page Systems skill: when to send a page and how to use pages well. Fetch it once at startup.
skill = urllib.request.urlopen("https://pagesystems.ai/v1/skill").read().decode()

async def main() -> None:
    async with MCPServerStreamableHttp(
        name="page-systems",
        params={
            "url": "https://pagesystems.ai/mcp",
            "headers": {"Authorization": f"Bearer {os.environ['PAGE_SYSTEMS_API_KEY']}"},
        },
        cache_tools_list=True,
    ) as page_systems:
        agent = Agent(name="Assistant", instructions=your_instructions + "\n\n" + skill, mcp_servers=[page_systems])
        result = await Runner.run(agent, user_message)
        print(result.final_output)
```

## 3. TypeScript

```bash
npm install @openai/agents
```

```ts
import { Agent, MCPServerStreamableHttp, run } from '@openai/agents';

const skill = await fetch('https://pagesystems.ai/v1/skill').then((r) => r.text()); // once, at startup
const pageSystems = new MCPServerStreamableHttp({
  name: 'page-systems',
  url: 'https://pagesystems.ai/mcp',
  requestInit: { headers: { Authorization: `Bearer ${process.env.PAGE_SYSTEMS_API_KEY}` } },
  cacheToolsList: true,
});
await pageSystems.connect();
try {
  const agent = new Agent({ name: 'Assistant', instructions: [yourInstructions, skill].join('\n\n'), mcpServers: [pageSystems] });
  const result = await run(agent, userMessage);
  console.log(result.finalOutput);
} finally {
  await pageSystems.close();
}
```

## 4. Keep the conversation

The answer arrives in a later turn, so pass the history back in: `result.to_input_list()` in Python, `result.history` in TypeScript, plus the new user message. The model then calls `get_page_result` with the page id it already has.
## 5. Check it works

Ask your agent something a page answers better than chat, for example "Ask Sam which of 9:00, 11:00 or 14:00 next Tuesday works for a call." It should send a link. Open it, pick a time, submit, then ask the agent what Sam picked: it reads the answer with `get_page_result`.