diff --git a/llama_stack/distribution/ui/app.py b/llama_stack/distribution/ui/app.py
index 77bb5ff6d..4ad05bb2d 100644
--- a/llama_stack/distribution/ui/app.py
+++ b/llama_stack/distribution/ui/app.py
@@ -21,10 +21,16 @@ def main():
     )
     rag_page = st.Page("page/playground/rag.py", title="RAG", icon="💬", default=False)
 
+    # Distribution pages
+    distribution_page = st.Page(
+        "page/distribution/distro.py", title="Distribution", icon="🔍", default=False
+    )
+
     pg = st.navigation(
         {
             "Evaluations": [application_evaluation_page],
             "Playground": [chat_page, rag_page],
+            "Distribution": [distribution_page],
         }
     )
     pg.run()
diff --git a/llama_stack/distribution/ui/page/distribution/distro.py b/llama_stack/distribution/ui/page/distribution/distro.py
new file mode 100644
index 000000000..0d16e801c
--- /dev/null
+++ b/llama_stack/distribution/ui/page/distribution/distro.py
@@ -0,0 +1,83 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import streamlit as st
+from modules.api import llama_stack_api
+
+st.title("🔍 Inspect Distribution")
+
+# API Section
+st.header("API Providers")
+apis_providers_info = llama_stack_api.client.providers.list()
+selected_api = st.selectbox("Select an API", list(apis_providers_info.keys()))
+st.dataframe([p.to_dict() for p in apis_providers_info[selected_api]], width=500)
+
+# for api in apis_providers_info:
+#     st.write(api)
+#     st.dataframe([p.to_dict() for p in apis_providers_info[api]], width=500)
+
+# Models Section
+st.header("Models")
+models_info = {m.identifier: m.to_dict() for m in llama_stack_api.client.models.list()}
+
+selected_model = st.selectbox("Select a model", list(models_info.keys()))
+st.json(models_info[selected_model])
+
+# Memory Banks Section
+st.header("Memory Banks")
+memory_banks_info = {
+    m.identifier: m.to_dict() for m in llama_stack_api.client.memory_banks.list()
+}
+
+if len(memory_banks_info) > 0:
+    selected_memory_bank = st.selectbox(
+        "Select a memory bank", list(memory_banks_info.keys())
+    )
+    st.json(memory_banks_info[selected_memory_bank])
+else:
+    st.info("No memory banks found")
+
+# Shields Section
+st.header("Shields")
+
+shields_info = {
+    s.identifier: s.to_dict() for s in llama_stack_api.client.shields.list()
+}
+
+selected_shield = st.selectbox("Select a shield", list(shields_info.keys()))
+st.json(shields_info[selected_shield])
+
+# Datasets Section
+st.header("Datasets")
+
+datasets_info = {
+    d.identifier: d.to_dict() for d in llama_stack_api.client.datasets.list()
+}
+
+selected_dataset = st.selectbox("Select a dataset", list(datasets_info.keys()))
+st.json(datasets_info[selected_dataset], expanded=False)
+
+# Scoring Functions Section
+st.header("Scoring Functions")
+
+scoring_functions_info = {
+    s.identifier: s.to_dict() for s in llama_stack_api.client.scoring_functions.list()
+}
+
+selected_scoring_function = st.selectbox(
+    "Select a scoring function", list(scoring_functions_info.keys())
+)
+st.json(scoring_functions_info[selected_scoring_function], expanded=False)
+
+# Eval Tasks Section
+st.header("Eval Tasks")
+
+eval_tasks_info = {
+    d.identifier: d.to_dict() for d in llama_stack_api.client.eval_tasks.list()
+}
+
+selected_eval_task = st.selectbox("Select an eval task", list(eval_tasks_info.keys()))
+st.json(eval_tasks_info[selected_eval_task], expanded=True)