Connect your AI agent to S4B
Give this to your AI
Copy this into your AI chat (Claude, ChatGPT, Gemini, or any MCP-compatible assistant) and hit send:
Go through https://mcp.s4b.be/sse and tell me what S4B does — trainings, hardware, consulting, everything.That's it. Your AI will browse our content and answer.
Change the question to anything you want — it has access to all our public pages.
Add to your IDE
Cursor — create or edit .cursor/mcp.json:
{
"mcpServers": {
"s4b-content": {
"url": "https://mcp.s4b.be/sse",
"transport": "sse"
}
}
}VS Code — create or edit .vscode/mcp.json:
{
"servers": {
"s4b-content": {
"url": "https://mcp.s4b.be/sse",
"type": "sse"
}
}
}
Integrate programmatically
Prerequisite: pip install mcp
import asyncio
from mcp import ClientSession
from mcp.client.sse import sse_client
async def main():
async with sse_client("https://mcp.s4b.be/sse") as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
print(f"{len(tools.tools)} tools available")
result = await session.call_tool("search_pages", {
"model": "claude-4-opus",
"query": "AI training"
})
print(result.content[0].text)
asyncio.run(main())
Available tools
All tools require the model parameter (e.g. "claude-4-opus").
| Tool | Description |
|---|---|
search_pages | Search public pages by title or content |
get_page | Get full content of a page by its URL slug |
list_pages | List public pages, optionally filtered by section |
list_glossary_terms | List AI glossary terms, filtered by letter |
list_trainings | List trainings from catalog, filtered by type |
get_training | Get full details of a training by reference |
list_sessions | List upcoming training sessions |
list_products | List products from catalog, filtered by type |
get_product | Get full details of a product by reference |
get_usage_stats | Get API usage statistics |
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