diff --git a/sklearn/fml/constants.py b/sklearn/fml/constants.py
index 1aa1bd3e7639c..fb98faf6b8bad 100644
--- a/sklearn/fml/constants.py
+++ b/sklearn/fml/constants.py
@@ -1,5 +1,6 @@
 class URI:
-    _SERVER = 'https://fmlearn.herokuapp.com/'
+    _SERVER = 'https://fmlearn.herokuapp.com'
+    _LOCAL = 'http://127.0.0.1:5000'
 
     _METRIC = '/metric'
     _RETRIEVE = '/retrieve'
@@ -7,6 +8,10 @@ class URI:
     _MIN = '/min'
     _ALL = '/all'
 
+    def __init__(self, debug=False):
+        if debug:
+            self._SERVER = self._LOCAL
+
     def post_metric(self):
         return self._SERVER + self._METRIC
 
diff --git a/sklearn/fml/fml_client.py b/sklearn/fml/fml_client.py
index 282acf686a8ff..44028a802ad01 100644
--- a/sklearn/fml/fml_client.py
+++ b/sklearn/fml/fml_client.py
@@ -22,7 +22,7 @@ def _post_msg(self, uri, data):
         print(res.status_code)
         return res.json()
 
-    def publish(self, model, metric_name, metric_value, dataset):
+    def publish(self, model, metric_name, metric_value, dataset, params=None):
         """
         Publishes the data collected to the federated meta learning API
         """
@@ -35,6 +35,16 @@ def publish(self, model, metric_name, metric_value, dataset):
         data['metric_name'] = metric_name
         data['metric_value'] = metric_value
         data['dataset_hash'] = dataset_hash
+        if params != None:
+            model_params = []
+            for key, value in params.items():
+                new_param = {}
+                new_param['param_name'] = str(key)
+                new_param['param_value'] = str(value)
+                model_params.append(new_param)
+            data['params'] = model_params
+        else:
+            data['params'] = ""
 
         return self._post_msg(URI().post_metric(), data)