diff --git a/docs/examples/index.md b/docs/examples/index.md
index 4781c3d7..447fa50e 100644
--- a/docs/examples/index.md
+++ b/docs/examples/index.md
@@ -68,6 +68,7 @@ Additionally, we have more comprehensive examples available in [The Swarms Cookb
 | Federated | [Federated Swarm](https://github.com/The-Swarm-Corporation/swarms-examples/blob/main/examples/structs/swarms/experimental/federated_swarm.py) | Distributed learning system with privacy-preserving agent collaboration |
 | Ant Colony | [Ant Swarm](https://github.com/The-Swarm-Corporation/swarms-examples/blob/main/examples/structs/swarms/experimental/ant_swarm.py) | Bio-inspired optimization using ant colony algorithms for agent coordination |
 | Matrix | [Agent Matrix](https://github.com/The-Swarm-Corporation/swarms-examples/blob/main/examples/structs/swarms/experimental/agent_matrix.py) | Grid-based agent organization for complex problem-solving |
+| MatrixSwarm | [MatrixSwarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/matrix_swarm_example.py) | Demonstrates transpose/add operations and running agents |
 | DFS | [DFS Search Swarm](https://github.com/The-Swarm-Corporation/swarms-examples/blob/main/examples/structs/swarms/experimental/dfs_search_swarm.py) | Depth-first search swarm for complex problem exploration |
 | Pulsar | [Pulsar Swarm](https://github.com/The-Swarm-Corporation/swarms-examples/blob/main/examples/structs/swarms/experimental/pulsar_swarm.py) | Pulsar-based coordination for synchronized agent behavior |
 
diff --git a/examples/multi_agent/matrix_swarm_example.py b/examples/multi_agent/matrix_swarm_example.py
new file mode 100644
index 00000000..fc6a48f5
--- /dev/null
+++ b/examples/multi_agent/matrix_swarm_example.py
@@ -0,0 +1,48 @@
+from swarms import Agent
+from swarms.structs.matrix_swarm import MatrixSwarm
+from swarms.prompts.finance_agent_sys_prompt import FINANCIAL_AGENT_SYS_PROMPT
+
+
+def create_agent(name: str) -> Agent:
+    """Utility function to build a simple agent for the matrix."""
+    return Agent(
+        agent_name=name,
+        system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
+        model_name="gpt-4o-mini",
+        max_loops=1,
+        streaming_on=False,
+        verbose=True,
+    )
+
+
+if __name__ == "__main__":
+    # Initialize a 2x2 matrix of agents
+    agents = [
+        [create_agent(f"Agent-{i}-{j}") for j in range(2)]
+        for i in range(2)
+    ]
+    swarm = MatrixSwarm(agents)
+
+    # Perform basic matrix operations
+    transposed = swarm.transpose()
+    added = swarm.add(transposed)
+
+    # Show shapes after operations
+    print("Original shape:", len(swarm.agents), len(swarm.agents[0]))
+    print("Transposed shape:", len(transposed.agents), len(transposed.agents[0]))
+    print("Added matrix shape:", len(added.agents), len(added.agents[0]))
+
+    # Prepare queries for each row of the matrix
+    queries = [
+        "What are the benefits of index funds?",
+        "How does compound interest work?",
+    ]
+
+    # Run agents by multiplying the matrix with its transpose
+    results = swarm.multiply(transposed, queries)
+
+    # Display results
+    for row in results:
+        for output in row:
+            print(f"{output.agent_name}: {output.output_result}")
+