ADD: ajout du mcp

csv_provider.py

@@ -0,0 +1,50 @@
+import asyncio
+import pandas as pd
+from huggingface_hub import HfApi, hf_hub_download
+from mcp.server import Server
+from mcp.types import Resource, ResourceResponse
+import os
+
+server = Server("csv-provider")
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
+api = HfApi()
+
+# Resource: csv://repo_id/path/to/file.csv
+@server.resource("csv://{repo_id}/{path}")
+async def get_csv(repo_id: str, path: str) -> ResourceResponse:
+    try:
+        # Télécharger le fichier CSV depuis le dataset privé
+        local_path = hf_hub_download(
+            repo_id=repo_id,
+            filename=path,
+            repo_type="dataset",
+            token=HF_TOKEN
+        )
+
+        # Charger et prévisualiser le CSV
+        df = pd.read_csv(local_path)
+        preview = df.head(5).to_string()
+
+        return ResourceResponse(
+            resource=Resource(
+                uri=f"csv://{repo_id}/{path}",
+                name=f"CSV: {path}",
+                description=f"Aperçu des données du dataset {repo_id}",
+                mimeType="text/plain",
+                text=preview,
+            )
+        )
+    except Exception as e:
+        return ResourceResponse(
+            resource=Resource(
+                uri=f"csv://{repo_id}/{path}",
+                name=f"Erreur CSV",
+                description=str(e),
+                mimeType="text/plain",
+                text=f"Impossible de lire {repo_id}/{path} : {e}",
+            )
+        )
+
+if __name__ == "__main__":
+    asyncio.run(server.run())

mcp.json

@@ -0,0 +1,10 @@
+{
+    "providers": {
+        "csv": {
+            "command": "python",
+            "args": [
+                "csv_provider.py"
+            ]
+        }
+    }
+}