diff --git a/mcp_server.py b/mcp_server.py
index 9f95d8c6..a04bb43d 100644
--- a/mcp_server.py
+++ b/mcp_server.py
@@ -55,19 +55,40 @@ HTTP_CLIENT = httpx.AsyncClient(timeout=60.0)
 
 # ==================== Agent系统配置 ====================
 
-# Kimi 配置 - 用于计划制定和深度推理
-KIMI_CONFIG = {
-    "api_key": "sk-TzB4VYJfCoXGcGrGMiewukVRzjuDsbVCkaZXi2LvkS8s60E5",
-    "base_url": "https://api.moonshot.cn/v1",
-    "model": "kimi-k2-thinking",  # 思考模型
+# ==================== 多模型配置 ====================
+
+# 模型配置字典（支持动态切换）
+MODEL_CONFIGS = {
+    "kimi-k2": {
+        "api_key": "sk-TzB4VYJfCoXGcGrGMiewukVRzjuDsbVCkaZXi2LvkS8s60E5",
+        "base_url": "https://api.moonshot.cn/v1",
+        "model": "moonshot-v1-8k",  # 快速模型
+    },
+    "kimi-k2-thinking": {
+        "api_key": "sk-TzB4VYJfCoXGcGrGMiewukVRzjuDsbVCkaZXi2LvkS8s60E5",
+        "base_url": "https://api.moonshot.cn/v1",
+        "model": "kimi-k2-thinking",  # 深度思考模型
+    },
+    "glm-4.6": {
+        "api_key": "",  # 需要配置智谱AI密钥
+        "base_url": "https://open.bigmodel.cn/api/paas/v4",
+        "model": "glm-4",
+    },
+    "deepmoney": {
+        "api_key": "",  # 空值
+        "base_url": "http://111.62.35.50:8000/v1",
+        "model": "deepmoney",
+    },
+    "gemini-3": {
+        "api_key": "",  # 需要配置Google API密钥
+        "base_url": "https://generativelanguage.googleapis.com/v1",
+        "model": "gemini-pro",
+    },
 }
 
-# DeepMoney 配置 - 用于新闻总结
-DEEPMONEY_CONFIG = {
-    "api_key": "",  # 空值
-    "base_url": "http://111.62.35.50:8000/v1",
-    "model": "deepmoney",
-}
+# 保持向后兼容的配置（默认使用 kimi-k2-thinking）
+KIMI_CONFIG = MODEL_CONFIGS["kimi-k2-thinking"]
+DEEPMONEY_CONFIG = MODEL_CONFIGS["deepmoney"]
 
 # ==================== MCP协议数据模型 ====================
 
@@ -143,6 +164,8 @@ class AgentChatRequest(BaseModel):
     user_avatar: Optional[str] = None  # 用户头像URL
     subscription_type: Optional[str] = None  # 用户订阅类型（free/pro/max）
     session_id: Optional[str] = None  # 会话ID（如果为空则创建新会话）
+    model: Optional[str] = "kimi-k2-thinking"  # 选择的模型（kimi-k2, kimi-k2-thinking, glm-4.6, deepmoney, gemini-3）
+    tools: Optional[List[str]] = None  # 选择的工具列表（工具名称数组，如果为None则使用全部工具）
 
 # ==================== MCP工具定义 ====================
 
@@ -1579,6 +1602,7 @@ class MCPAgentIntegrated:
         user_nickname: str = None,
         user_avatar: str = None,
         cookies: dict = None,
+        model_config: dict = None,  # 新增：动态模型配置
     ) -> AsyncGenerator[str, None]:
         """主流程（流式输出）- 逐步返回执行结果"""
         logger.info(f"[Agent Stream] 处理查询: {user_query}")
@@ -1586,11 +1610,24 @@ class MCPAgentIntegrated:
         # 将 cookies 存储为实例属性，供工具调用时使用
         self.cookies = cookies or {}
 
+        # 如果传入了自定义模型配置，使用自定义配置，否则使用默认的 Kimi
+        if model_config:
+            planning_client = OpenAI(
+                api_key=model_config["api_key"],
+                base_url=model_config["base_url"],
+            )
+            planning_model = model_config["model"]
+            logger.info(f"[Agent Stream] 使用自定义模型: {planning_model}")
+        else:
+            planning_client = self.kimi_client
+            planning_model = self.kimi_model
+            logger.info(f"[Agent Stream] 使用默认模型: {planning_model}")
+
         try:
             # 发送开始事件
             yield self._format_sse("status", {"stage": "start", "message": "开始处理查询"})
 
-            # 阶段1: Kimi 制定计划（流式，带 DeepMoney 备选）
+            # 阶段1: 使用选中的模型制定计划（流式，带 DeepMoney 备选）
             yield self._format_sse("status", {"stage": "planning", "message": "正在制定执行计划..."})
 
             messages = [
@@ -1603,9 +1640,9 @@ class MCPAgentIntegrated:
             use_fallback = False
 
             try:
-                # 尝试使用 Kimi 流式 API
-                stream = self.kimi_client.chat.completions.create(
-                    model=self.kimi_model,
+                # 尝试使用选中的模型流式 API
+                stream = planning_client.chat.completions.create(
+                    model=planning_model,
                     messages=messages,
                     temperature=1.0,
                     max_tokens=16000,
@@ -2165,11 +2202,12 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
     except Exception as e:
         logger.error(f"[ES] 保存用户消息失败: {e}")
 
-    # 获取工具列表
-    tools = [tool.dict() for tool in TOOLS]
+    # ==================== 动态工具过滤 ====================
+    # 获取所有可用工具
+    all_tools = [tool.dict() for tool in TOOLS]
 
     # 添加特殊工具：summarize_news
-    tools.append({
+    all_tools.append({
         "name": "summarize_news",
         "description": "使用 DeepMoney 模型总结新闻数据，提取关键信息",
         "parameters": {
@@ -2188,6 +2226,21 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
         }
     })
 
+    # 如果用户指定了工具列表，则进行过滤
+    if chat_request.tools is not None and len(chat_request.tools) > 0:
+        selected_tool_names = set(chat_request.tools)
+        tools = [tool for tool in all_tools if tool["name"] in selected_tool_names]
+        logger.info(f"[工具过滤] 用户选择了 {len(tools)}/{len(all_tools)} 个工具: {selected_tool_names}")
+    else:
+        # 默认使用全部工具
+        tools = all_tools
+        logger.info(f"[工具过滤] 使用全部 {len(tools)} 个工具")
+
+    # ==================== 动态模型选择 ====================
+    selected_model = chat_request.model or "kimi-k2-thinking"
+    model_config = MODEL_CONFIGS.get(selected_model, MODEL_CONFIGS["kimi-k2-thinking"])
+    logger.info(f"[模型选择] 使用模型: {selected_model} ({model_config['model']})")
+
     # 返回流式响应
     return StreamingResponse(
         agent.process_query_stream(
@@ -2199,6 +2252,7 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
             user_nickname=chat_request.user_nickname,
             user_avatar=chat_request.user_avatar,
             cookies=cookies,  # 传递 cookies 用于认证 API 调用
+            model_config=model_config,  # 传递选中的模型配置
         ),
         media_type="text/event-stream",
         headers={