fix(mcp): expand JVM system properties in stdio args/env/cwd

mateclaw-server/src/main/java/vip/mate/llm/chatgpt/ChatGPTChatModel.java

@@ -5,6 +5,8 @@ import org.springframework.ai.chat.messages.AssistantMessage;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.ChatResponseMetadata;
+import org.springframework.ai.chat.metadata.DefaultUsage;
+import org.springframework.ai.chat.metadata.Usage;
 import org.springframework.ai.chat.model.ChatModel;
 import org.springframework.ai.chat.model.ChatResponse;
 import org.springframework.ai.chat.model.Generation;
@@ -110,7 +112,22 @@ public class ChatGPTChatModel implements ChatModel {
                             return null;
                         }
                         case "done" -> {
-                            // 流结束，如果没有任何 tool call 产生过 done event 但有未完成的，忽略
+                            // Emit a final empty-content ChatResponse carrying the
+                            // usage metadata so NodeStreamingChatHelper can record
+                            // per-turn token counts. Without this the OAuth path's
+                            // turns log 0/0/0 (the client only knows about Usage
+                            // when it's attached to a ChatResponse.metadata).
+                            if (event.inputTokens() != null || event.outputTokens() != null
+                                    || event.totalTokens() != null) {
+                                int in = event.inputTokens() != null ? event.inputTokens() : 0;
+                                int out = event.outputTokens() != null ? event.outputTokens() : 0;
+                                int total = event.totalTokens() != null ? event.totalTokens() : (in + out);
+                                Usage usage = new DefaultUsage(in, out, total);
+                                Generation usageGen = new Generation(new AssistantMessage(""),
+                                        ChatGenerationMetadata.builder().finishReason("stop").build());
+                                return new ChatResponse(List.of(usageGen),
+                                        ChatResponseMetadata.builder().model(model).usage(usage).build());
+                            }
                             return null;
                         }
                         default -> { return null; }

mateclaw-server/src/main/java/vip/mate/llm/chatgpt/ChatGPTResponsesClient.java

@@ -37,12 +37,17 @@ public class ChatGPTResponsesClient {
     /**
      * 流式调用结果 — 包含文本增量和 tool call 事件
      */
-    public record StreamEvent(String type, String content, String toolCallId, String toolName, String toolArgsDelta) {
+    public record StreamEvent(String type, String content, String toolCallId, String toolName, String toolArgsDelta,
-        public static StreamEvent text(String delta) { return new StreamEvent("text", delta, null, null, null); }
+                              Integer inputTokens, Integer outputTokens, Integer totalTokens) {
-        public static StreamEvent toolCallStart(String callId, String name) { return new StreamEvent("tool_call_start", null, callId, name, null); }
+        public static StreamEvent text(String delta) { return new StreamEvent("text", delta, null, null, null, null, null, null); }
-        public static StreamEvent toolCallArgsDelta(String callId, String delta) { return new StreamEvent("tool_call_args_delta", null, callId, null, delta); }
+        public static StreamEvent toolCallStart(String callId, String name) { return new StreamEvent("tool_call_start", null, callId, name, null, null, null, null); }
-        public static StreamEvent toolCallDone(String callId, String args) { return new StreamEvent("tool_call_done", null, callId, null, args); }
+        public static StreamEvent toolCallArgsDelta(String callId, String delta) { return new StreamEvent("tool_call_args_delta", null, callId, null, delta, null, null, null); }
-        public static StreamEvent done() { return new StreamEvent("done", null, null, null, null); }
+        public static StreamEvent toolCallDone(String callId, String args) { return new StreamEvent("tool_call_done", null, callId, null, args, null, null, null); }
+        public static StreamEvent done() { return new StreamEvent("done", null, null, null, null, null, null, null); }
+        /** Done event carrying token usage extracted from {@code response.completed.response.usage}. */
+        public static StreamEvent done(Integer in, Integer out, Integer total) {
+            return new StreamEvent("done", null, null, null, null, in, out, total);
+        }
     }
 
     /**
@@ -281,8 +286,25 @@ public class ChatGPTResponsesClient {
                 return StreamEvent.toolCallDone(callId, args);
             }
 
-            // 完成/结束
+            // 完成/结束 — extract usage from response.completed so the agent
+            // pipeline can record per-turn token counts (otherwise OAuth turns
+            // get logged as 0/0/0). Field shape mirrors the upstream client:
+            // input_tokens → prompt, output_tokens → completion, total_tokens
+            // falls back to (input + output) when the API omits it.
             if (type.startsWith("response.completed") || type.startsWith("response.done")) {
+                JsonNode usage = node.path("response").path("usage");
+                if (!usage.isMissingNode() && !usage.isNull()) {
+                    Integer in = usage.has("input_tokens") ? usage.get("input_tokens").asInt() : null;
+                    Integer out = usage.has("output_tokens") ? usage.get("output_tokens").asInt() : null;
+                    Integer total = usage.has("total_tokens")
+                            ? usage.get("total_tokens").asInt()
+                            : (in != null && out != null ? in + out : null);
+                    if (in != null || out != null || total != null) {
+                        log.debug("[ChatGPT] Usage in response.completed: input={}, output={}, total={}",
+                                in, out, total);
+                        return StreamEvent.done(in, out, total);
+                    }
+                }
                 return StreamEvent.done();
             }
 

mateclaw-server/src/main/java/vip/mate/tool/mcp/runtime/McpClientManager.java

@@ -269,6 +269,7 @@ public class McpClientManager {
         // Args
         if (server.getArgsJson() != null && !server.getArgsJson().isBlank()) {
             List<String> args = JSONUtil.toList(server.getArgsJson(), String.class);
+            args = args.stream().map(McpClientManager::expandEnvVars).toList();
             builder.args(args);
         }
 
@@ -376,17 +377,22 @@ public class McpClientManager {
     }
 
     /**
-     * 展开环境变量引用，如 ${ENV_VAR} 或 $ENV_VAR
+     * 展开系统属性和环境变量引用，如 ${user.home}、${ENV_VAR} 或 $ENV_VAR
      * <p>
-     * 先处理 ${VAR}（精确匹配），再用正则处理 $VAR（word boundary），
+     * 先处理 ${VAR}（精确匹配，JVM 系统属性优先于环境变量，
-     * 避免 $PATH 误替换 $PATH_HOME 的问题。
+     * 这样 ${user.home} 等跨平台占位符在 Windows 上也能解析），
+     * 再用正则处理 $VAR（word boundary），避免 $PATH 误替换 $PATH_HOME 的问题。
      */
     private static String expandEnvVars(String value) {
         if (value == null || !value.contains("$")) {
             return value;
         }
         String result = value;
-        // Phase 1: 精确匹配 ${VAR} 模式（不会误替换）
+        // Phase 1a: ${VAR} 优先匹配 JVM system property（如 ${user.home}、${java.io.tmpdir}）
+        for (String key : System.getProperties().stringPropertyNames()) {
+            result = result.replace("${" + key + "}", System.getProperty(key));
+        }
+        // Phase 1b: ${VAR} 回退匹配 OS 环境变量
         for (Map.Entry<String, String> env : System.getenv().entrySet()) {
             result = result.replace("${" + env.getKey() + "}", env.getValue());
         }