diff --git a/dr_agent/mcp_backend/main.py b/dr_agent/mcp_backend/main.py
index ef3a201..44918ca 100644
--- a/dr_agent/mcp_backend/main.py
+++ b/dr_agent/mcp_backend/main.py
@@ -1,6 +1,7 @@
 import argparse
 import asyncio
 import os
+import uuid
 from typing import TYPE_CHECKING, Annotated, List, Optional
 
 import aiohttp
@@ -33,6 +34,36 @@
 
 dotenv.load_dotenv()
 
+
+def _url_to_snippet_id(url: str) -> str:
+    """Generate a deterministic short snippet ID from a URL using UUID5."""
+    return str(uuid.uuid5(uuid.NAMESPACE_URL, url))[:8]
+
+
+def _assign_snippet_ids(items: list, url_fn) -> list:
+    """Add a unique snippet_id to each item based on its URL.
+
+    Args:
+        items: List of result dicts to annotate.
+        url_fn: Callable that extracts the URL string from an item.
+
+    If multiple items share the same URL (e.g. multiple snippets from one paper),
+    a ``-<counter>`` suffix is appended to keep IDs unique within the list.
+    """
+    seen: dict[str, int] = {}
+    for item in items:
+        url = url_fn(item) or ""
+        if url:
+            base_id = _url_to_snippet_id(url)
+        else:
+            base_id = str(uuid.uuid4())[:8]
+
+        count = seen.get(base_id, 0)
+        seen[base_id] = count + 1
+        item["snippet_id"] = f"{base_id}-{count}" if count > 0 else base_id
+    return items
+
+
 mcp = FastMCP(
     "RL-RAG MCP",
     include_tags=os.environ.get("MCP_INCLUDE_TAGS", "search,browse,rerank").split(","),
@@ -80,6 +111,9 @@ def semantic_scholar_search(
         limit=min(limit, 100),  # Ensure limit doesn't exceed API maximum
     )
 
+    if "data" in results and results["data"]:
+        _assign_snippet_ids(results["data"], lambda item: item.get("url"))
+
     return results
 
 
@@ -128,6 +162,12 @@ def semantic_scholar_snippet_search(
         limit=limit,
     )
 
+    if "data" in results and results["data"]:
+        _assign_snippet_ids(
+            results["data"],
+            lambda item: item.get("paper", {}).get("url"),
+        )
+
     return results
 
 
@@ -166,6 +206,9 @@ def pubmed_search(
         offset=offset,
     )
 
+    if "data" in results and results["data"]:
+        _assign_snippet_ids(results["data"], lambda item: item.get("url"))
+
     return results
 
 
@@ -254,6 +297,11 @@ def massive_serve_search(
         for result in parsed_results
     ]
 
+    # massive_serve results don't have URLs; generate IDs from doc_id
+    for item in response["data"]:
+        doc_id_str = str(item.get("doc_id", ""))
+        item["snippet_id"] = _url_to_snippet_id(doc_id_str)
+
     return response
 
 
@@ -281,6 +329,9 @@ def serper_google_webpage_search(
         query=query, num_results=num_results, search_type="search", gl=gl, hl=hl
     )
 
+    if "organic" in results and results["organic"]:
+        _assign_snippet_ids(results["organic"], lambda item: item.get("link"))
+
     return results
 
 
@@ -310,6 +361,7 @@ def serper_fetch_webpage_content(
 
         return {
             **result,
+            "snippet_id": _url_to_snippet_id(webpage_url),
             "success": True,
         }
     except Exception as e:
@@ -318,6 +370,7 @@ def serper_fetch_webpage_content(
             "markdown": "",
             "metadata": {},
             "url": webpage_url,
+            "snippet_id": _url_to_snippet_id(webpage_url),
             "success": False,
             "error": str(e),
         }
@@ -347,6 +400,8 @@ def jina_fetch_webpage_content(
         - error: Error message if fetch failed
     """
     result = fetch_webpage_content_jina(url=webpage_url, timeout=timeout)
+    if isinstance(result, dict):
+        result["snippet_id"] = _url_to_snippet_id(webpage_url)
     return result
 
 
@@ -367,6 +422,9 @@ def serper_google_scholar_search(
         num_results=num_results,
     )
 
+    if "organic" in results and results["organic"]:
+        _assign_snippet_ids(results["organic"], lambda item: item.get("link"))
+
     return results
 
 
@@ -410,7 +468,9 @@ async def crawl4ai_fetch_webpage_content(
         timeout_ms=timeout_ms,
         include_html=include_html,
     )
-    return result
+    result_dict = result.model_dump() if hasattr(result, "model_dump") else dict(result)
+    result_dict["snippet_id"] = _url_to_snippet_id(url)
+    return result_dict
 
 
 @mcp.tool(tags={"browse", "necessary"})
@@ -463,7 +523,9 @@ async def crawl4ai_docker_fetch_webpage_content(
         use_pruning=use_pruning,
         timeout_ms=timeout_ms,
     )
-    return result
+    result_dict = result.model_dump() if hasattr(result, "model_dump") else dict(result)
+    result_dict["snippet_id"] = _url_to_snippet_id(url)
+    return result_dict
 
 
 @mcp.tool(tags={"browse"})
@@ -491,7 +553,7 @@ def webthinker_fetch_webpage_content(
         keep_links=keep_links,
     )
 
-    return {"url": url, "text": text}
+    return {"url": url, "text": text, "snippet_id": _url_to_snippet_id(url)}
 
 
 @mcp.tool(tags={"browse"})
@@ -538,7 +600,7 @@ async def webthinker_fetch_webpage_content_async(
             keep_links=keep_links,
         )
 
-    return {"url": url, "text": text}
+    return {"url": url, "text": text, "snippet_id": _url_to_snippet_id(url)}
 
 
 if __name__ == "__main__":