feat: event research mcp

event_research.py

@@ -0,0 +1,36 @@
+from mcp.server.fastmcp import FastMCP
+from playwright.sync_api import sync_playwright
+from bs4 import BeautifulSoup
+import pandas as pd
+
+mcp = FastMCP(name="Event research", stateless_http=True)
+
+@mcp.tool(description="Analyze all games from the last 30 days and return behavioral patterns")
+def get_chess_event():
+    url = "https://www.echecsfrance.com/en/tournaments"
+
+    with sync_playwright() as p:
+        browser = p.chromium.launch(headless=True)
+        page = browser.new_page()
+        print(f"🌐 Chargement de {url} ...")
+        page.goto(url, timeout=60000)
+        page.wait_for_timeout(5000)  # attendre le rendu JS
+        html = page.content()
+        browser.close()
+
+    soup = BeautifulSoup(html, "html.parser")
+    table = soup.find("table")
+
+    if not table:
+        print("❌ Aucun tableau trouvé dans le DOM final")
+        return None
+
+    headers = [th.text.strip() for th in table.find_all("th")]
+    rows = [
+        [td.text.strip() for td in tr.find_all("td")]
+        for tr in table.find_all("tr")[1:]
+        if tr.find_all("td")
+    ]
+
+    df = pd.DataFrame(rows, columns=headers)
+    return df.to_json()

requirements.txt

@@ -64,3 +64,5 @@ typing_extensions==4.15.0
 urllib3==2.5.0
 uvicorn==0.35.0
 Werkzeug==3.1.1
+pandas,
+bs4,

server.py

@@ -5,6 +5,7 @@ from fastapi.staticfiles import StaticFiles
 from fastapi.templating import Jinja2Templates
 from echo_server import mcp as echo_mcp
 from math_server import mcp as math_mcp
+from event_research import mcp as event_research_mcp
 import os
 
 
@@ -14,6 +15,7 @@ async def lifespan(app: FastAPI):
     async with contextlib.AsyncExitStack() as stack:
         await stack.enter_async_context(echo_mcp.session_manager.run())
         await stack.enter_async_context(math_mcp.session_manager.run())
+        await stack.enter_async_context(event_research_mcp.session_manager.run())
         yield