feat: add MCP integration for MemoryService

manifest.json

@@ -0,0 +1,86 @@
+{
+  "manifest_version": "0.3",
+  "name": "memU",
+  "display_name": "memU - AI Memory Service",
+  "version": "1.0.0",
+  "description": "memU is a memory framework built for 24/7 proactive agents. It is designed for long-running use and greatly reduces the LLM token cost of keeping agents always online, making always-on, evolving agents practical in production systems. memU continuously captures and understands user intent. Even without a command, the agent can tell what you are about to do and act on it by itself.",
+  "author": {
+    "name": "NevaMind-AI",
+    "email": "jinshen.yin@nevamind.ai"
+  },
+  "homepage": "https://github.com/NevaMind-AI/memU",
+  "documentation": "https://memu.pro/docs",
+  "server": {
+    "type": "python",
+    "entry_point": "src/memu/integrations/mcp.py",
+    "mcp_config": {
+      "command": "uvx",
+      "args": [
+        "--from",
+        "memu-py[mcp] @ git+https://github.com/De13ruyne/memU@feat/add_mcp",
+        "memu-mcp"
+      ],
+      "env": {
+        "OPENAI_API_KEY": "${user_config.api_key}"
+      }
+    }
+  },
+  "tools": [
+    {
+      "name": "memorize",
+      "description": "Save conversations, documents, or knowledge to memory"
+    },
+    {
+      "name": "retrieve",
+      "description": "Search for relevant memories based on a query"
+    },
+    {
+      "name": "list_memories",
+      "description": "List all stored memory items for a user"
+    },
+    {
+      "name": "list_categories",
+      "description": "List all memory categories for a user"
+    },
+    {
+      "name": "create_memory",
+      "description": "Manually create a memory item"
+    },
+    {
+      "name": "update_memory",
+      "description": "Update an existing memory item"
+    },
+    {
+      "name": "delete_memory",
+      "description": "Delete a specific memory item"
+    },
+    {
+      "name": "clear_memory",
+      "description": "Clear all memories for a user"
+    }
+  ],
+  "user_config": {
+    "api_key": {
+      "type": "string",
+      "title": "LLM API Key",
+      "description": "OpenAI-compatible API key for chat and embedding",
+      "required": true,
+      "sensitive": true
+    }
+  },
+  "keywords": [
+    "memory",
+    "ai",
+    "agent",
+    "llm",
+    "conversation",
+    "knowledge",
+    "proactive",
+    "mcp"
+  ],
+  "license": "MIT",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/NevaMind-AI/memU"
+  }
+}

pyproject.toml

@@ -70,6 +70,7 @@ test = [
 postgres = ["pgvector>=0.3.4", "sqlalchemy[postgresql-psycopgbinary]>=2.0.36"]
 langgraph = ["langgraph>=0.0.10", "langchain-core>=0.1.0"]
 claude = ["claude-agent-sdk>=0.1.24"]
+mcp = ["mcp>=1.0", "python-dotenv>=1.0"]
 
 [project.urls]
 "Homepage" = "https://github.com/NevaMind-AI/MemU"
@@ -78,10 +79,12 @@ claude = ["claude-agent-sdk>=0.1.24"]
 
 [project.scripts]
 memu-server = "memu.server.cli:main"
+memu-mcp = "memu.integrations.mcp:main"
 
 [tool.deptry.per_rule_ignores]
+DEP001 = ["dotenv"]
 # Optional dependencies used in examples/
-DEP002 = ["claude-agent-sdk"]
+DEP002 = ["claude-agent-sdk", "mcp", "python-dotenv"]
 
 [tool.mypy]
 files = ["src", "tests"]
@@ -109,6 +112,14 @@ ignore_missing_imports = true
 module = ["pgvector.*"]
 ignore_missing_imports = true
 
+[[tool.mypy.overrides]]
+module = ["mcp.*"]
+ignore_missing_imports = true
+
+[[tool.mypy.overrides]]
+module = ["dotenv.*"]
+ignore_missing_imports = true
+
 [[tool.mypy.overrides]]
 module = ["memu.client.openai_wrapper"]
 disallow_untyped_defs = false

src/memu/app/crud.py

@@ -510,6 +510,7 @@ async def _patch_create_memory_item(self, state: WorkflowState, step_context: An
         content_embedding = (await self._get_step_embedding_client(step_context).embed(embed_payload))[0]
 
         item = store.memory_item_repo.create_item(
+            resource_id="",
             memory_type=memory_payload["type"],
             summary=memory_payload["content"],
             embedding=content_embedding,

src/memu/integrations/__init__.py

@@ -1,3 +1,13 @@
-from .langgraph import MemULangGraphTools
+from typing import Any
+
+
+def __getattr__(name: str) -> Any:
+    if name == "MemULangGraphTools":
+        from .langgraph import MemULangGraphTools
+
+        return MemULangGraphTools
+    msg = f"module {__name__!r} has no attribute {name!r}"
+    raise AttributeError(msg)
+
 
 __all__ = ["MemULangGraphTools"]