diff --git a/src/ragas/metrics/__init__.py b/src/ragas/metrics/__init__.py
index ebf92ebbc..77b6e7b60 100644
--- a/src/ragas/metrics/__init__.py
+++ b/src/ragas/metrics/__init__.py
@@ -62,7 +62,7 @@
     StringPresence,
 )
 from ragas.metrics._summarization import SummarizationScore, summarization_score
-from ragas.metrics._tool_call_accuracy import ToolCallAccuracy
+from ragas.metrics._tool_call_accuracy import ToolCallAccuracy, ToolCallParallelAccuracy
 from ragas.metrics._topic_adherence import TopicAdherenceScore
 
 __all__ = [
@@ -108,6 +108,7 @@
     "AgentGoalAccuracyWithoutReference",
     "AgentGoalAccuracyWithReference",
     "ToolCallAccuracy",
+    "ToolCallParallelAccuracy",
     "ResponseRelevancy",
     "SemanticSimilarity",
     "DistanceMeasure",
diff --git a/src/ragas/metrics/_tool_call_accuracy.py b/src/ragas/metrics/_tool_call_accuracy.py
index b89a23b49..695a22bbf 100644
--- a/src/ragas/metrics/_tool_call_accuracy.py
+++ b/src/ragas/metrics/_tool_call_accuracy.py
@@ -5,7 +5,7 @@
 from dataclasses import dataclass, field
 
 from ragas.dataset_schema import MultiTurnSample, SingleTurnSample
-from ragas.messages import AIMessage
+from ragas.messages import AIMessage, ToolCall
 from ragas.metrics._string import ExactMatch
 from ragas.metrics.base import MetricType, MultiTurnMetric, SingleTurnMetric
 
@@ -33,7 +33,7 @@ def init(self, run_config):
         pass
 
     async def _get_arg_score(
-        self, preds: t.Dict[str, t.Any], refs: t.Dict[str, t.Any], callbacks: Callbacks
+            self, preds: t.Dict[str, t.Any], refs: t.Dict[str, t.Any], callbacks: Callbacks
     ) -> float:
         score = 0.0
         for arg in refs.keys():
@@ -48,7 +48,7 @@ async def _get_arg_score(
         return score / len(refs.keys())
 
     def is_sequence_aligned(
-        self, pred_sequence: t.List[str], ref_sequence: t.List[str]
+            self, pred_sequence: t.List[str], ref_sequence: t.List[str]
     ) -> bool:
         ref_index = 0  # Index to track position in reference sequence
         for pred in pred_sequence:
@@ -82,13 +82,12 @@ async def _multi_turn_ascore(
         if pred_tool_calls:
             score = 0.0
             reference_tool_calls = sample.reference_tool_calls
-            for ref_tool_call in reference_tool_calls:
-                for pred_tool_call in pred_tool_calls:
-                    if ref_tool_call.name == pred_tool_call.name:
-                        arg_score = await self._get_arg_score(
-                            pred_tool_call.args, ref_tool_call.args, callbacks
-                        )
-                        score += arg_score
+            for ref_tool_call, pred_tool_call in zip(reference_tool_calls, pred_tool_calls):
+                if ref_tool_call.name == pred_tool_call.name:
+                    arg_score = await self._get_arg_score(
+                        pred_tool_call.args, ref_tool_call.args, callbacks
+                    )
+                    score += arg_score
 
             score /= len(reference_tool_calls)
         else:
@@ -99,3 +98,59 @@ async def _multi_turn_ascore(
 
     async def _ascore(self, row: t.Dict, callbacks: Callbacks) -> float:
         return await self._multi_turn_ascore(MultiTurnSample(**row), callbacks)
+
+
+@dataclass
+class ToolCallParallelAccuracy(ToolCallAccuracy):
+    name: str = "tool_call_parallel_accuracy"
+
+    @staticmethod
+    def _sorted_key_for_tool_call(tc: ToolCall):
+        key_list = [tc.name]
+        args = tc.args
+        args_name = sorted(args)
+        for name in args_name:
+            key_list.append(name)
+            key_list.append(str(args[name]))
+
+        return tuple(key_list)
+
+    async def _multi_turn_ascore(
+            self, sample: MultiTurnSample, callbacks: Callbacks
+    ) -> float:
+        assert (sample.reference_tool_calls is not None), "Reference tool calls is not set"
+
+        pred_tool_calls = []
+        for item in sample.user_input:
+            if isinstance(item, AIMessage) and item.tool_calls is not None:
+                pred_tool_calls.extend(item.tool_calls)
+
+        # Sort the tool calls first.
+        pred_tool_calls = sorted(pred_tool_calls, key=self._sorted_key_for_tool_call)
+        reference_tool_calls = sorted(sample.reference_tool_calls, key=self._sorted_key_for_tool_call)
+
+        tool_call_pred_sequence = [tool_call.name for tool_call in pred_tool_calls]
+        tool_call_ref_sequence = [
+            tool_call.name for tool_call in reference_tool_calls
+        ]
+
+        sequence_aligned = int(
+            self.is_sequence_aligned(tool_call_pred_sequence, tool_call_ref_sequence)
+        )
+
+        if pred_tool_calls:
+            score = 0.0
+            reference_tool_calls = reference_tool_calls
+            for ref_tool_call, pred_tool_call in zip(reference_tool_calls, pred_tool_calls):
+                if ref_tool_call.name == pred_tool_call.name:
+                    arg_score = await self._get_arg_score(
+                        pred_tool_call.args, ref_tool_call.args, callbacks
+                    )
+                    score += arg_score
+
+            score /= len(reference_tool_calls)
+        else:
+            warnings.warn("No tool calls found in the user input")
+            return 0.0
+
+        return score * sequence_aligned