diff --git a/examples/synap_memory.py b/examples/synap_memory.py
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+#!/usr/bin/env python3
+"""Example: Synap memory integration.
+
+Demonstrates how to give a Claude Agent persistent, cross-session memory using
+Synap (https://maximem.ai) — a managed memory layer for AI agents.
+
+Two plug points:
+  1. `create_synap_hooks` — installs a `UserPromptSubmit` hook that fetches
+     relevant Synap context for each prompt and injects it via
+     `additionalContext`. Optionally records the user prompt for future recall.
+  2. `create_synap_mcp_server` — exposes `synap_search` and `synap_remember`
+     as MCP tools the model can call explicitly.
+
+Install:
+    pip install maximem-synap-claude-agent maximem-synap
+
+Set `SYNAP_API_KEY` in your environment. Get a free key at
+https://synap.maximem.ai.
+
+Open source: https://github.com/maximem-ai/maximem_synap_sdk
+"""
+
+import asyncio
+import os
+
+from claude_agent_sdk import ClaudeAgentOptions, query
+from maximem_synap import MaximemSynapSDK
+from synap_claude_agent import create_synap_hooks, create_synap_mcp_server
+
+
+async def main() -> None:
+    sdk = MaximemSynapSDK(api_key=os.environ["SYNAP_API_KEY"])
+    await sdk.initialize()
+
+    user_id = "demo-user-001"
+    customer_id = "demo-customer"
+
+    # Pattern 1 — automatic context injection via hook
+    print("=== Hook-based context injection ===")
+    async for message in query(
+        prompt="What did I tell you about my dietary preferences?",
+        options=ClaudeAgentOptions(
+            hooks=create_synap_hooks(sdk, user_id=user_id, customer_id=customer_id),
+        ),
+    ):
+        print(message)
+
+    # Pattern 2 — explicit search / remember via MCP tools
+    print("\n=== MCP tool-based memory access ===")
+    options = ClaudeAgentOptions(
+        mcp_servers={
+            "synap": create_synap_mcp_server(
+                sdk, user_id=user_id, customer_id=customer_id
+            ),
+        },
+        allowed_tools=["mcp__synap__synap_search", "mcp__synap__synap_remember"],
+    )
+    async for message in query(
+        prompt="Remember that I prefer concise answers, then search my memory.",
+        options=options,
+    ):
+        print(message)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())