diff --git a/README.md b/README.md
index a9746a0a..27a00aa6 100644
--- a/README.md
+++ b/README.md
@@ -17,6 +17,8 @@
 
 语析是一个功能强大的智能问答平台，融合了 RAG 知识库与知识图谱技术，基于 LangGraph + Vue.js + FastAPI + LightRAG 架构构建。
 
+---
+
 🙏 感谢 Star ~ ⭐⭐⭐⭐⭐
 
 详细文档请查看全新的 [**📄文档中心**](https://xerrors.github.io/Yuxi-Know/)， [📽️ 点击查看视频演示 v0.2](https://www.bilibili.com/video/BV1ETedzREgY/?share_source=copy_web&vd_source=37b0bdbf95b72ea38b2dc959cfadc4d8)
diff --git a/server/routers/chat_router.py b/server/routers/chat_router.py
index 9ec98af4..f0d93b33 100644
--- a/server/routers/chat_router.py
+++ b/server/routers/chat_router.py
@@ -408,8 +408,11 @@ async def get_tools(agent_id: str, current_user: User = Depends(get_required_use
     if not (agent := agent_manager.get_agent(agent_id)):
         raise HTTPException(status_code=404, detail=f"智能体 {agent_id} 不存在")
 
-    if hasattr(agent, "get_tools"):
-        tools = agent.get_tools()
+    if hasattr(agent, "get_tools") and callable(agent.get_tools):
+        if asyncio.iscoroutinefunction(agent.get_tools):
+            tools = await agent.get_tools()
+        else:
+            tools = agent.get_tools()
     else:
         tools = get_buildin_tools()
 
diff --git a/src/agents/common/mcp.py b/src/agents/common/mcp.py
index 60476461..1fa36171 100644
--- a/src/agents/common/mcp.py
+++ b/src/agents/common/mcp.py
@@ -58,7 +58,7 @@ async def get_mcp_client(
         return None
 
 
-async def get_mcp_tools(server_name: str) -> list[Callable[..., Any]]:
+async def get_mcp_tools(server_name: str, additional_servers: dict[str, dict] = None) -> list[Callable[..., Any]]:
     """Get MCP tools for a specific server, initializing client if needed."""
     global _mcp_tools_cache
 
@@ -66,9 +66,11 @@ async def get_mcp_tools(server_name: str) -> list[Callable[..., Any]]:
     if server_name in _mcp_tools_cache:
         return _mcp_tools_cache[server_name]
 
+    mcp_servers = MCP_SERVERS | (additional_servers or {})
+
     try:
-        assert server_name in MCP_SERVERS, f"Server {server_name} not found in MCP_SERVERS"
-        client = await get_mcp_client({server_name: MCP_SERVERS[server_name]})
+        assert server_name in mcp_servers, f"Server {server_name} not found in MCP_SERVERS"
+        client = await get_mcp_client({server_name: mcp_servers[server_name]})
         if client is None:
             return []
 
@@ -86,7 +88,6 @@ async def get_mcp_tools(server_name: str) -> list[Callable[..., Any]]:
         logger.error(f"Failed to load tools from MCP server '{server_name}': {e}")
         return []
 
-
 async def get_all_mcp_tools() -> list[Callable[..., Any]]:
     """Get all tools from all configured MCP servers."""
     all_tools = []
diff --git a/src/agents/common/toolkits/mysql/tools.py b/src/agents/common/toolkits/mysql/tools.py
index 8e86c27e..d4bb401a 100644
--- a/src/agents/common/toolkits/mysql/tools.py
+++ b/src/agents/common/toolkits/mysql/tools.py
@@ -44,7 +44,7 @@ class TableListModel(BaseModel):
     pass
 
 
-@tool(args_schema=TableListModel)
+@tool(name_or_callable="查询表名", args_schema=TableListModel)
 def mysql_list_tables() -> str:
     """获取数据库中的所有表名
 
@@ -94,7 +94,7 @@ class TableDescribeModel(BaseModel):
     table_name: str = Field(description="要查询的表名", example="users")
 
 
-@tool(args_schema=TableDescribeModel)
+@tool(name_or_callable="描述表", args_schema=TableDescribeModel)
 def mysql_describe_table(table_name: Annotated[str, "要查询结构的表名"]) -> str:
     """获取指定表的详细结构信息
 
@@ -168,7 +168,7 @@ class QueryModel(BaseModel):
     timeout: int | None = Field(default=10, description="查询超时时间（秒），默认10秒，最大60秒", ge=1, le=60)
 
 
-@tool(args_schema=QueryModel)
+@tool(name_or_callable="执行 SQL 查询", args_schema=QueryModel)
 def mysql_query(
     sql: Annotated[str, "要执行的SQL查询语句（只能是SELECT语句）"],
     limit: Annotated[int | None, "限制返回的最大行数，默认100，最大1000"] = 100,
diff --git a/src/agents/common/tools.py b/src/agents/common/tools.py
index 0023d9b8..7d9fa2aa 100644
--- a/src/agents/common/tools.py
+++ b/src/agents/common/tools.py
@@ -146,7 +146,11 @@ def gen_tool_info(tools) -> list[dict[str, Any]]:
                 }
 
                 if hasattr(tool_obj, "args_schema") and tool_obj.args_schema:
-                    schema = tool_obj.args_schema.schema()
+                    if isinstance(tool_obj.args_schema, dict):
+                        schema = tool_obj.args_schema
+                    else:
+                        schema = tool_obj.args_schema.schema()
+
                     for arg_name, arg_info in schema.get("properties", {}).items():
                         info["args"].append(
                             {
@@ -161,7 +165,8 @@ def gen_tool_info(tools) -> list[dict[str, Any]]:
 
             except Exception as e:
                 logger.error(
-                    f"Failed to process tool {getattr(tool_obj, 'name', 'unknown')}: {e}\n{traceback.format_exc()}"
+                    f"Failed to process tool {getattr(tool_obj, 'name', 'unknown')}: {e}\n{traceback.format_exc()}. "
+                    f"Details: {dict(tool_obj.__dict__)}"
                 )
                 continue
 
diff --git a/src/agents/react/graph.py b/src/agents/react/graph.py
index 831905fb..eb79c87a 100644
--- a/src/agents/react/graph.py
+++ b/src/agents/react/graph.py
@@ -3,14 +3,11 @@ from pathlib import Path
 from langchain.agents import create_agent
 from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call
 
-from src import config as sys_config
 from src.agents.common.base import BaseAgent
 from src.agents.common.models import load_chat_model
 from src.agents.common.tools import get_buildin_tools
 from src.utils import logger
 
-model = load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507")
-
 
 @dynamic_prompt
 def context_aware_prompt(request: ModelRequest) -> str:
@@ -34,9 +31,6 @@ class ReActAgent(BaseAgent):
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
-        self.graph = None
-        self.workdir = Path(sys_config.save_dir) / "agents" / self.module_name
-        self.workdir.mkdir(parents=True, exist_ok=True)
 
     def get_tools(self):
         return get_buildin_tools()
@@ -47,12 +41,11 @@ class ReActAgent(BaseAgent):
 
         # 创建 ReActAgent
         graph = create_agent(
-            model=model,
+            model=load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507"),  # 实际会被覆盖
             tools=self.get_tools(),
             middleware=[context_aware_prompt, context_based_model],
             checkpointer=await self._get_checkpointer(),
         )
 
         self.graph = graph
-        logger.info("ReActAgent 使用内存 checkpointer 构建成功")
         return graph
diff --git a/src/agents/reporter/__init__.py b/src/agents/reporter/__init__.py
new file mode 100644
index 00000000..03af7748
--- /dev/null
+++ b/src/agents/reporter/__init__.py
@@ -0,0 +1,4 @@
+from .graph import SqlReporterAgent
+
+
+__all__ = ["SqlReporterAgent"]
diff --git a/src/agents/reporter/graph.py b/src/agents/reporter/graph.py
new file mode 100644
index 00000000..8402722a
--- /dev/null
+++ b/src/agents/reporter/graph.py
@@ -0,0 +1,67 @@
+import textwrap
+from pathlib import Path
+
+from langchain.agents import create_agent
+from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call
+
+from src.agents.common.base import BaseAgent
+from src.agents.common.models import load_chat_model
+from src.agents.common.mcp import get_mcp_tools
+from src.agents.common.toolkits.mysql import get_mysql_tools
+from src.utils import logger
+
+_mcp_servers = {
+    "mcp-server-chart": {
+        "url": "https://mcp.api-inference.modelscope.net/9993ae42524c4c/mcp",
+        "transport": "streamable_http",
+    },
+}
+
+@dynamic_prompt
+def context_aware_prompt(request: ModelRequest) -> str:
+    user_prompt = request.runtime.context.system_prompt
+    agent_prompt = user_prompt + textwrap.dedent("""
+        You are an SQL reporting assistant. Your task is to generate SQL queries based on user requests
+        and provide insights from the database. Use the tools provided to you to answer the questions.
+        """)
+
+    return agent_prompt
+
+
+@wrap_model_call
+async def context_based_model(request: ModelRequest, handler) -> ModelResponse:
+    # 从 runtime context 读取配置
+    model_spec = request.runtime.context.model
+    model = load_chat_model(model_spec)
+
+    request = request.override(model=model)
+    return await handler(request)
+
+
+class SqlReporterAgent(BaseAgent):
+    name = "SQL 报告助手"
+    description = "一个能够生成 SQL 查询报告的智能体助手。同时调用 Charts MCP 生成图表。"
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def get_tools(self):
+        chart_tools = await get_mcp_tools("mcp-server-chart", additional_servers=_mcp_servers)
+        mysql_tools = get_mysql_tools()
+        return chart_tools + mysql_tools
+
+    async def get_graph(self, **kwargs):
+        if self.graph:
+            return self.graph
+
+        # 创建 SqlReporterAgent
+        graph = create_agent(
+            model=load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507"),
+            tools=await self.get_tools(),
+            middleware=[context_aware_prompt, context_based_model],
+            checkpointer=await self._get_checkpointer(),
+        )
+
+        self.graph = graph
+        logger.info("SqlReporterAgent 构建成功")
+        return graph
\ No newline at end of file