feat: solution for 'Повторный экзамен: FAQ-бот — ChromaDB + один MCP-tool'

src/mcp_tool.py

@@ -0,0 +1,18 @@
+from typing import List, Dict
+
+from .vector_store import QdrantVectorStore
+
+
+class MCPTool:
+    """
+    A simple tool that uses the vector store to answer queries.
+    """
+
+    def __init__(self, vector_store: QdrantVectorStore):
+        self.vector_store = vector_store
+
+    def answer(self, query: str, top_k: int = 3) -> List[Dict]:
+        """
+        Return the top_k most relevant documents for the query.
+        """
+        return self.vector_store.search(query, top_k=top_k)