Release v0.7.1

dispatch_cli/mcp/client.py

@@ -14,6 +14,7 @@
     EventTraceResponse,
     GetScheduleRequest,
     GetScheduleResponse,
+    ListLongTermMemoriesResponse,
     ListSchedulesRequest,
     ListSchedulesResponse,
     RebootAgentResponse,
@@ -270,6 +271,16 @@ def get_invocation_history(
         resp.raise_for_status()
         return resp.json()
 
+    # Memory Operations
+    def list_long_term_memories(
+        self, agent_name: str, namespace: str
+    ) -> ListLongTermMemoriesResponse:
+        """List all long-term memories for an agent."""
+        url = self._namespaced_url(f"/memory/long-term/agent/{agent_name}", namespace)
+        resp = self.client.get(url)
+        resp.raise_for_status()
+        return ListLongTermMemoriesResponse.model_validate(resp.json())
+
     # Async Invoke Operations (for MCP tools that need non-blocking behavior)
     async def invoke_function_async(
         self,

dispatch_cli/mcp/models.py

@@ -225,3 +225,23 @@ class EventTraceResponse(BaseModel):
         description="Tree-structured events with invocation enrichment"
     )
     llm_summary: dict[str, Any] | None = None
+
+
+# Memory Models
+
+
+class MemoryEntry(BaseModel):
+    """A single long-term memory entry."""
+
+    mem_key: str = Field(description="Memory key")
+    mem_value: str = Field(description="Memory value")
+    last_updated: str | None = Field(
+        default=None, description="Last update timestamp (ISO 8601)"
+    )
+
+
+class ListLongTermMemoriesResponse(BaseModel):
+    """Response from listing long-term memories."""
+
+    agent_name: str = Field(description="Agent name")
+    memories: list[MemoryEntry] = Field(description="List of memory entries")

dispatch_cli/mcp/operator/tools.py

@@ -32,6 +32,7 @@
     EventTraceResponse,
     GetScheduleRequest,
     GetScheduleResponse,
+    ListLongTermMemoriesResponse,
     ListSchedulesRequest,
     ListSchedulesResponse,
     RebootAgentResponse,
@@ -537,6 +538,15 @@ class ReadLocalAgentLogsResponse(BaseModel):
     total_lines: int = Field(description="Total number of lines retrieved")
 
 
+class ListLongTermMemoriesRequest(BaseModel):
+    """Request payload for listing long-term memories."""
+
+    agent_name: str = Field(description="Agent name")
+    namespace: str = Field(
+        description="Namespace the agent belongs to. Use list_namespaces to discover valid namespaces."
+    )
+
+
 # Helper functions for testable core logic
 
 
@@ -805,13 +815,19 @@ async def my_function(payload: MyInput) -> MyOutput:
 # Retrieve data
 value = await memory.long_term.get(mem_key="user_prefs")
 
+# List all memories for the agent
+all_memories = await memory.long_term.list()
+
 # Delete data
 await memory.long_term.delete(mem_key="user_prefs")
 
 # Override agent_name if needed (e.g., reading another agent's data)
 value = await memory.long_term.get(mem_key="user_prefs", agent_name="other-agent")
+all_memories = await memory.long_term.list(agent_name="other-agent")
 ```
 
+You can also use the `list_long_term_memories` MCP tool to inspect an agent's memories.
+
 ### Short-term Memory (Session Store)
 ```python
 # Store session data
@@ -1421,6 +1437,23 @@ async def get_invocation_status(
             completed_at=result.get("completed_at"),
         )
 
+    @mcp.tool()
+    async def list_long_term_memories(
+        request: ListLongTermMemoriesRequest,
+    ) -> ListLongTermMemoriesResponse:
+        """List all long-term memories for an agent.
+
+        Returns all key-value pairs stored in the agent's long-term memory.
+
+        Args:
+            request: ListLongTermMemoriesRequest with agent_name and namespace
+
+        Returns:
+            ListLongTermMemoriesResponse with agent_name and list of memory entries
+        """
+        ns = _get_namespace(request.namespace)
+        return client.list_long_term_memories(request.agent_name, namespace=ns)
+
     @mcp.tool()
     async def start_local_agent_dev(
         request: StartLocalAgentDevRequest,
@@ -2196,7 +2229,7 @@ async def submit_feedback(
         """
         async_client = await client._get_async_client()
         response = await async_client.post(
-            client._global_url("/api/unstable/feedback/"),
+            client._global_url("/feedback/"),
             json=request.model_dump(),
         )
         response.raise_for_status()

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "dispatch-cli"
-version = "0.6.0"
+version = "0.7.1"
 description = ""
 authors = [
     {name = "Diamond Bishop", email = "diamond.bishop@datadoghq.com"},
@@ -34,7 +34,7 @@ dependencies = [
 ]
 
 [tool.uv.sources]
-dispatch_agents = {git = "https://github.com/datadog-labs/dispatch_agents_sdk", tag = "v0.9.0"}
+dispatch_agents = {git = "https://github.com/datadog-labs/dispatch_agents_sdk", tag = "v0.10.0"}
 
 [dependency-groups]
 dev = [