diff --git a/.env.example b/.env.example
index e378447..ca81864 100644
--- a/.env.example
+++ b/.env.example
@@ -1,4 +1,15 @@
-LLM_MODEL_TYPE = "deepseek"
-LLM_API_URL = "https://api.deepseek.com"
-LLM_API_KEY = "sk-xxxxxxxxxxxxxxxxxx"
-LLM_MODEL_NAME = "deepseek-chat"
+# --- Anthropic (for anthropic_mcp_client.py - Claude native tool calling) ---
+# Option 1: set the key directly
+ANTHROPIC_API_KEY=sk-ant-xxxxxxxxxxxxxxxx
+# Option 2: reference a shell env var (dotenv expands ${VAR} from environment)
+# ANTHROPIC_API_KEY=${ANTHROPIC_KEY}
+LLM_MODEL_NAME=claude-sonnet-4-20250514
+
+# --- OpenAI-compatible (for simple_mcp_client.py / mcp_chatbot) ---
+LLM_MODEL_TYPE=openai
+LLM_API_URL=https://api.openai.com/v1
+LLM_API_KEY=sk-xxxxxxxxxxxxxxxx
+# LLM_MODEL_TYPE=deepseek
+# LLM_API_URL=https://api.deepseek.com
+# LLM_API_KEY=sk-xxxxxxxxxxxxxxxxxx
+# LLM_MODEL_NAME=deepseek-chat
diff --git a/.gitignore b/.gitignore
index 48abf26..e806a65 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,3 +21,16 @@ bak/*
 simple_mcp_client_stream.py
 mcp_chatbot_termial.py
 mcp_chatbot_stream.py
+
+# Script/terminal recording artifacts
+typescript
+^C
+
+# Data files (user-provided, not committed)
+data/*.json
+!data/.gitkeep
+
+# IDE
+.idea/
+.vscode/
+*.swp
diff --git a/anthropic_mcp_client.py b/anthropic_mcp_client.py
new file mode 100644
index 0000000..9c514df
--- /dev/null
+++ b/anthropic_mcp_client.py
@@ -0,0 +1,226 @@
+#!/usr/bin/env python3
+"""MCP Client using Anthropic Claude for tool calling.
+
+Usage:
+    # Direct server script:
+    python anthropic_mcp_client.py services/time_service.py
+
+    # Via config file:
+    python anthropic_mcp_client.py get_current_time config/mcp_config.json
+
+Requires ANTHROPIC_API_KEY in .env or environment.
+"""
+
+import asyncio
+import json
+import os
+import sys
+from contextlib import AsyncExitStack
+from typing import Any, Dict, List, Optional
+
+import anthropic
+from dotenv import load_dotenv
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+from pathlib import Path
+
+# Load .env from script dir (project root) — dotenv loads relative to CWD by default
+_PROJECT_ROOT = Path(__file__).resolve().parent
+load_dotenv(_PROJECT_ROOT / ".env")
+
+
+class AnthropicMCPClient:
+    def __init__(
+        self,
+        api_key: str,
+        model_name: str = "claude-sonnet-4-20250514",
+        max_tokens: int = 4096,
+    ):
+        self.model_name = model_name
+        self.max_tokens = max_tokens
+        self.session: Optional[ClientSession] = None
+        self.exit_stack = AsyncExitStack()
+        self._cleanup_lock = asyncio.Lock()
+
+        self.available_tools: List[Dict[str, Any]] = []
+        self.anthropic_tools: List[Dict[str, Any]] = []
+
+        self.client = anthropic.AsyncAnthropic(api_key=api_key)
+
+    @staticmethod
+    def parse_arguments(args: List[str]) -> StdioServerParameters:
+        """Parse CLI args into StdioServerParameters."""
+        if len(args) == 1:
+            server_script = args[0]
+            if not server_script.endswith((".py", ".js")):
+                raise ValueError("Server script must be .py or .js")
+            command = "python" if server_script.endswith(".py") else "node"
+            return StdioServerParameters(command=command, args=[server_script], env=None)
+        elif len(args) == 2:
+            server_id, config_path = args
+            with open(config_path) as f:
+                config = json.load(f)
+            srv = config.get("mcpServers", {}).get(server_id)
+            if not srv:
+                raise ValueError(f"Server '{server_id}' not found in config")
+            return StdioServerParameters(
+                command=srv["command"], args=srv["args"], env=None
+            )
+        else:
+            raise ValueError(
+                "Usage: python anthropic_mcp_client.py <script.py>\n"
+                "   or: python anthropic_mcp_client.py <server_id> <config.json>"
+            )
+
+    async def connect_to_server(self, server_params: StdioServerParameters):
+        """Connect to an MCP server via stdio."""
+        transport = await self.exit_stack.enter_async_context(
+            stdio_client(server_params)
+        )
+        reader, writer = transport
+        self.session = await self.exit_stack.enter_async_context(
+            ClientSession(reader, writer)
+        )
+        await self.session.initialize()
+
+        # Discover tools
+        tools_resp = await self.session.list_tools()
+        for tool in tools_resp.tools:
+            # Store in Anthropic tool format
+            self.anthropic_tools.append(
+                {
+                    "name": tool.name,
+                    "description": tool.description or "",
+                    "input_schema": tool.inputSchema,
+                }
+            )
+
+        tool_names = [t["name"] for t in self.anthropic_tools]
+        print(f"[SYS] Connected. Available tools: {tool_names}")
+
+    async def process_query(self, query: str) -> str:
+        """Send query to Claude, handle tool calls, return final response."""
+        messages = [{"role": "user", "content": query}]
+
+        while True:
+            resp = await self.client.messages.create(
+                model=self.model_name,
+                max_tokens=self.max_tokens,
+                tools=self.anthropic_tools,
+                messages=messages,
+            )
+
+            # Check if Claude wants to use tools
+            if resp.stop_reason == "tool_use":
+                # Collect all content blocks (text + tool_use)
+                assistant_content = []
+                for block in resp.content:
+                    if block.type == "text":
+                        assistant_content.append(
+                            {"type": "text", "text": block.text}
+                        )
+                    elif block.type == "tool_use":
+                        assistant_content.append(
+                            {
+                                "type": "tool_use",
+                                "id": block.id,
+                                "name": block.name,
+                                "input": block.input,
+                            }
+                        )
+
+                messages.append({"role": "assistant", "content": assistant_content})
+
+                # Execute each tool call
+                tool_results = []
+                for block in resp.content:
+                    if block.type == "tool_use":
+                        print(f"[TOOL] Calling {block.name}({block.input})")
+                        result = await self.session.call_tool(block.name, block.input)
+                        result_text = (
+                            result.content[0].text
+                            if result.content
+                            else "No result"
+                        )
+                        print(f"[TOOL] {block.name} -> {result_text[:200]}")
+                        tool_results.append(
+                            {
+                                "type": "tool_result",
+                                "tool_use_id": block.id,
+                                "content": result_text,
+                            }
+                        )
+
+                messages.append({"role": "user", "content": tool_results})
+                continue  # Let Claude process the tool results
+
+            # No more tool calls — extract final text
+            text_parts = [b.text for b in resp.content if b.type == "text"]
+            return "\n".join(text_parts) if text_parts else "(no response)"
+
+    async def chat_loop(self):
+        """Interactive REPL."""
+        print("[SYS] MCP Client ready. Type your query (or 'quit' to exit).\n")
+        loop = asyncio.get_event_loop()
+
+        while True:
+            try:
+                query = await loop.run_in_executor(
+                    None, lambda: input("[YOU]: ").strip()
+                )
+                if not query:
+                    continue
+                if query.lower() in ("quit", "exit", "q"):
+                    break
+
+                response = await self.process_query(query)
+                print(f"\n[Claude]: {response}\n")
+
+            except (KeyboardInterrupt, EOFError):
+                print("\n[SYS] Shutting down...")
+                break
+            except Exception as e:
+                print(f"\n[ERR] {e}\n")
+
+    async def cleanup(self):
+        async with self._cleanup_lock:
+            try:
+                await self.exit_stack.aclose()
+                self.session = None
+            except Exception as e:
+                print(f"[ERR] Cleanup error: {e}")
+
+
+async def main():
+    try:
+        server_params = AnthropicMCPClient.parse_arguments(sys.argv[1:])
+    except ValueError as e:
+        print(f"[ERR] {e}")
+        sys.exit(1)
+
+    api_key = (
+        os.getenv("ANTHROPIC_API_KEY")
+        or os.getenv("ANTHROPIC_KEY")
+        or ""
+    )
+    model = os.getenv("LLM_MODEL_NAME", "claude-sonnet-4-20250514")
+
+    if not api_key:
+        print("[ERR] ANTHROPIC_API_KEY or ANTHROPIC_KEY not set. Add to .env or environment.")
+        sys.exit(1)
+
+    print(f"[SYS] Model: {model}")
+
+    client = AnthropicMCPClient(api_key=api_key, model_name=model)
+
+    try:
+        await client.connect_to_server(server_params)
+        await client.chat_loop()
+    except Exception as e:
+        print(f"\n[ERR] {e}")
+    finally:
+        await client.cleanup()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/config/mcp_config.json b/config/mcp_config.json
new file mode 100644
index 0000000..b69ea6d
--- /dev/null
+++ b/config/mcp_config.json
@@ -0,0 +1,20 @@
+{
+    "mcpServers": {
+        "time": {
+            "command": "python",
+            "args": ["services/time_service.py"]
+        },
+        "weather": {
+            "command": "python",
+            "args": ["services/weather_service_us.py"]
+        },
+        "calculator": {
+            "command": "python",
+            "args": ["services/calculator_service.py"]
+        },
+        "devops": {
+            "command": "python",
+            "args": ["services/devops_knowledge_service.py"]
+        }
+    }
+}
diff --git a/config/server_config.json b/config/server_config.json
index 9a3686f..884d044 100644
--- a/config/server_config.json
+++ b/config/server_config.json
@@ -1,30 +1,54 @@
 {
     "mcpServers": {
       "get_current_time": {
-        "name": "时间",
+        "name": "Time",
         "type": "stdio",
-        "description": "获取时间",
+        "description": "Get current time in any timezone",
         "command": "uv",
         "args": [
           "--directory",
-          "E:/04Code/llm/tiny-mcp/services",
+          "./services",
           "run",
           "time_service.py"
         ]
       },
-      "get_weather": {
-        "name": "天气",
+      "get_weather_us": {
+        "name": "Weather US",
         "type": "stdio",
-        "description": "获取国内天气",
+        "description": "Get US weather forecasts and alerts (NWS API, no key needed)",
         "command": "uv",
         "args": [
           "--directory",
-          "E:/04Code/llm/tiny-mcp/services",
+          "./services",
           "run",
-          "weather_service_zh.py"
+          "weather_service_us.py"
+        ]
+      },
+      "calculator": {
+        "name": "Calculator",
+        "type": "stdio",
+        "description": "Math calculations and unit conversions",
+        "command": "uv",
+        "args": [
+          "--directory",
+          "./services",
+          "run",
+          "calculator_service.py"
+        ]
+      },
+      "devops_knowledge": {
+        "name": "DevOps & LLM Knowledge",
+        "type": "stdio",
+        "description": "DevOps/SRE and LLM interview Q&A search",
+        "command": "uv",
+        "args": [
+          "--directory",
+          ".",
+          "run",
+          "services/devops_knowledge_service.py"
         ]
       }
     },
     "defaultServer": "get_current_time",
-    "system": "自定义系统提示词"
-}
\ No newline at end of file
+    "system": "You are a helpful assistant with access to tools for time, weather, and math."
+}
diff --git a/data/.gitkeep b/data/.gitkeep
new file mode 100644
index 0000000..e69de29
diff --git a/mcp_chatbot/__init__.py b/mcp_chatbot/__init__.py
index 5f5e81e..244ccf2 100644
--- a/mcp_chatbot/__init__.py
+++ b/mcp_chatbot/__init__.py
@@ -2,4 +2,11 @@
 from .chat.chat_session import ChatSession
 from .llm.llm_service import LLMService
 from .mcp.mcp_client import MCPClient
-from .mcp.mcp_tool import MCPTool
\ No newline at end of file
+from .mcp.mcp_tool import MCPTool
+
+# Lazy import to avoid circular dependency; main lives in mcp_chatbot_main.py
+def __getattr__(name: str):
+    if name == "main":
+        from mcp_chatbot_main import main
+        return main
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
\ No newline at end of file
diff --git a/mcp_chatbot/__main__.py b/mcp_chatbot/__main__.py
new file mode 100644
index 0000000..69bab62
--- /dev/null
+++ b/mcp_chatbot/__main__.py
@@ -0,0 +1,12 @@
+"""Allow running as: python -m mcp_chatbot"""
+import asyncio
+
+from mcp_chatbot_main import main
+
+if __name__ == "__main__":
+    import platform
+    if platform.system().lower() == "windows":
+        loop = asyncio.get_event_loop()
+        loop.run_until_complete(main())
+    else:
+        asyncio.run(main())
diff --git a/mcp_chatbot/chat/__init__.py b/mcp_chatbot/chat/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/mcp_chatbot/chat/chat_session.py b/mcp_chatbot/chat/chat_session.py
index 34b1439..1a398db 100644
--- a/mcp_chatbot/chat/chat_session.py
+++ b/mcp_chatbot/chat/chat_session.py
@@ -330,10 +330,10 @@ async def get_llm_response_stream_with_tool_call(
             tool_calls = []
             for idx, tool_call_data in enumerate(tool_call_data_list):
                 tool_name = tool_call_data["tool"]
-                argments = tool_call_data["arguments"]
+                arguments = tool_call_data["arguments"]
 
                 yield ("tool_call", tool_name)
-                yield ("tool_arguments", json.dumps(argments))
+                yield ("tool_arguments", json.dumps(arguments))
 
                 # 执行工具调用
                 yield ("tool_execution", f"Executing tool {tool_name} ...")
diff --git a/mcp_chatbot/config/__init__.py b/mcp_chatbot/config/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/mcp_chatbot/config/configuration.py b/mcp_chatbot/config/configuration.py
index a7ca394..da9a7ef 100644
--- a/mcp_chatbot/config/configuration.py
+++ b/mcp_chatbot/config/configuration.py
@@ -1,11 +1,14 @@
 import json
 import os
+from pathlib import Path
 from dotenv import load_dotenv
 from typing import Any, Optional
 
+# Load .env from project root (two levels up from this file)
+_PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
 load_dotenv(
-    dotenv_path=".env", 
-    override=True
+    dotenv_path=_PROJECT_ROOT / ".env",
+    override=True,
 )
 
 class Configuration:
diff --git a/mcp_chatbot/llm/__init__.py b/mcp_chatbot/llm/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/mcp_chatbot/mcp/__init__.py b/mcp_chatbot/mcp/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/mcp_chatbot/mcp/mcp_client.py b/mcp_chatbot/mcp/mcp_client.py
index 44e6224..7ee4d7b 100644
--- a/mcp_chatbot/mcp/mcp_client.py
+++ b/mcp_chatbot/mcp/mcp_client.py
@@ -94,9 +94,7 @@ async def list_tools(self) -> list[Any]:
         tools_response = await self.session.list_tools()
         return [
             MCPTool(tool.name, tool.description, tool.inputSchema)
-            for item in tools_response
-            if isinstance(item, tuple) and item[0] == "tools"
-            for tool in item[1]  # 解析工具数据
+            for tool in tools_response.tools
         ]
     
     async def execute_tool(
diff --git a/mcp_chatbot/mcp/mcp_tool.py b/mcp_chatbot/mcp/mcp_tool.py
index 8d3c746..f139312 100644
--- a/mcp_chatbot/mcp/mcp_tool.py
+++ b/mcp_chatbot/mcp/mcp_tool.py
@@ -2,7 +2,7 @@
 
 
 class MCPTool:
-    """ MCP 工具, 更壮工具信息
+    """ MCP 工具, 封装工具信息
     """
     def __init__(
         self, 
diff --git a/mcp_chatbot_main.py b/mcp_chatbot_main.py
index ca24017..c0e457c 100644
--- a/mcp_chatbot_main.py
+++ b/mcp_chatbot_main.py
@@ -1,25 +1,26 @@
 import asyncio
-import json
+from pathlib import Path
 
 from mcp_chatbot import Configuration, ChatSession, LLMService, MCPClient
 
 async def main() -> None:
     """主入口函数
     """
-    config = Configuration()
-    config.print_config()
-    server_config = config.load_config("config/server_config.json")  # 加载服务器配置
+    cfg = Configuration()
+    cfg.print_config()
+    config_path = Path(__file__).resolve().parent / "config" / "server_config.json"
+    server_config = cfg.load_config(str(config_path))  # 加载服务器配置
 
     servers = [
-        MCPClient(name, config)
-        for name, config in server_config["mcpServers"].items()  # 创建服务器实例
+        MCPClient(name, svc_cfg)
+        for name, svc_cfg in server_config["mcpServers"].items()  # 创建服务器实例
     ]
 
     llm_service = LLMService(
-        api_key=config.llm_api_key,
-        model_name=config.model_name,
-        base_url=config.base_url,
-        model_type=config.model_type,
+        api_key=cfg.llm_api_key,
+        model_name=cfg.model_name,
+        base_url=cfg.base_url,
+        model_type=cfg.model_type,
     )
 
     chat_session = ChatSession(servers, llm_service)
diff --git a/mcp_http_bridge.py b/mcp_http_bridge.py
new file mode 100644
index 0000000..a7581c4
--- /dev/null
+++ b/mcp_http_bridge.py
@@ -0,0 +1,286 @@
+#!/usr/bin/env python3
+"""MCP HTTP Bridge — expose MCP tools as REST endpoints for a web UI.
+
+Spawns MCP services as stdio subprocesses, connects via the MCP SDK,
+and serves tool listing / chat / direct-tool-call over HTTP.
+
+Usage:
+    # Start the bridge (default port 8100):
+    python mcp_http_bridge.py
+
+    # Or with uvicorn:
+    uvicorn mcp_http_bridge:app --host 0.0.0.0 --port 8100
+
+Env vars:
+    MCP_BRIDGE_PORT       — listen port (default 8100)
+    MCP_CONFIG            — path to server_config.json (default config/server_config.json)
+    LLM_API_KEY           — OpenAI-compatible API key
+    LLM_API_URL           — base URL for LLM API
+    LLM_MODEL_NAME        — model name
+    LLM_MODEL_TYPE        — 'openai' | 'deepseek' | 'ollama'
+"""
+
+import asyncio
+import json
+import os
+from contextlib import AsyncExitStack, asynccontextmanager
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from dotenv import load_dotenv
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+from openai import AsyncOpenAI
+from pydantic import BaseModel
+
+_PROJECT_ROOT = Path(__file__).resolve().parent
+load_dotenv(_PROJECT_ROOT / ".env")
+
+# ---------------------------------------------------------------------------
+# Request / Response schemas
+# ---------------------------------------------------------------------------
+
+class ChatRequest(BaseModel):
+    query: str
+    history: Optional[List[Dict[str, str]]] = None
+
+class ChatResponse(BaseModel):
+    answer: str
+    tool_calls: List[Dict[str, Any]] = []
+
+class ToolCallRequest(BaseModel):
+    tool: str
+    arguments: Dict[str, Any] = {}
+
+class ToolCallResponse(BaseModel):
+    result: str
+    is_error: bool = False
+
+class ToolInfo(BaseModel):
+    name: str
+    description: str
+    parameters: Dict[str, Any]
+    server: str
+
+# ---------------------------------------------------------------------------
+# MCP Connection Manager
+# ---------------------------------------------------------------------------
+
+class MCPBridge:
+    """Manages stdio connections to MCP servers and provides tool access."""
+
+    def __init__(self):
+        self.exit_stack = AsyncExitStack()
+        self.sessions: Dict[str, ClientSession] = {}
+        self.tools: List[ToolInfo] = []
+        self._tool_server: Dict[str, str] = {}  # tool_name -> server_name
+        self._tool_session: Dict[str, ClientSession] = {}  # tool_name -> session
+        self.llm_client: Optional[AsyncOpenAI] = None
+        self.model_name: str = ""
+
+    async def start(self, config_path: str):
+        """Load config and connect to all MCP servers."""
+        with open(config_path) as f:
+            config = json.load(f)
+
+        servers = config.get("mcpServers", {})
+
+        for name, srv in servers.items():
+            try:
+                command = srv["command"]
+                args = srv.get("args", [])
+
+                params = StdioServerParameters(
+                    command=command, args=args, env=None
+                )
+                transport = await self.exit_stack.enter_async_context(
+                    stdio_client(params)
+                )
+                reader, writer = transport
+                session = await self.exit_stack.enter_async_context(
+                    ClientSession(reader, writer)
+                )
+                await session.initialize()
+                self.sessions[name] = session
+
+                # Discover tools
+                tools_resp = await session.list_tools()
+                for tool in tools_resp.tools:
+                    info = ToolInfo(
+                        name=tool.name,
+                        description=tool.description or "",
+                        parameters=tool.inputSchema,
+                        server=name,
+                    )
+                    self.tools.append(info)
+                    self._tool_server[tool.name] = name
+                    self._tool_session[tool.name] = session
+
+                print(f"[MCP] Connected: {name} ({len(tools_resp.tools)} tools)")
+            except Exception as e:
+                print(f"[MCP] Failed to connect {name}: {e}")
+
+        # Init LLM client
+        api_key = os.getenv("LLM_API_KEY", "")
+        base_url = os.getenv("LLM_API_URL", "")
+        model_type = os.getenv("LLM_MODEL_TYPE", "deepseek")
+        self.model_name = os.getenv("LLM_MODEL_NAME", "deepseek-chat")
+
+        if api_key:
+            self.llm_client = AsyncOpenAI(
+                api_key=api_key,
+                base_url=None if model_type == "openai" else base_url,
+            )
+
+        print(f"[MCP] Bridge ready — {len(self.tools)} tools from {len(self.sessions)} servers")
+
+    async def stop(self):
+        await self.exit_stack.aclose()
+
+    async def call_tool(self, tool_name: str, arguments: Dict[str, Any]) -> str:
+        session = self._tool_session.get(tool_name)
+        if not session:
+            raise ValueError(f"Unknown tool: {tool_name}")
+        result = await session.call_tool(tool_name, arguments)
+        if result.content:
+            return result.content[0].text
+        return "(no result)"
+
+    async def chat(self, query: str, history: Optional[List[Dict[str, str]]] = None) -> ChatResponse:
+        """Send query through LLM with MCP tools available."""
+        if not self.llm_client:
+            raise ValueError("LLM not configured — set LLM_API_KEY in .env")
+
+        # Build OpenAI-format tool definitions
+        oai_tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": t.name,
+                    "description": t.description,
+                    "parameters": t.parameters,
+                },
+            }
+            for t in self.tools
+        ]
+
+        messages: List[Dict[str, Any]] = []
+        if history:
+            messages.extend(history)
+        messages.append({"role": "user", "content": query})
+
+        tool_calls_log: List[Dict[str, Any]] = []
+
+        # LLM tool-call loop (max 5 rounds)
+        for _ in range(5):
+            resp = await self.llm_client.chat.completions.create(
+                model=self.model_name,
+                messages=messages,
+                tools=oai_tools if oai_tools else None,
+                tool_choice="auto" if oai_tools else None,
+            )
+            msg = resp.choices[0].message
+            messages.append(msg)
+
+            if not msg.tool_calls:
+                return ChatResponse(answer=msg.content or "", tool_calls=tool_calls_log)
+
+            for tc in msg.tool_calls:
+                fn_name = tc.function.name
+                try:
+                    fn_args = json.loads(tc.function.arguments) if isinstance(tc.function.arguments, str) else tc.function.arguments
+                except json.JSONDecodeError:
+                    fn_args = {"input": tc.function.arguments}
+
+                try:
+                    result_text = await self.call_tool(fn_name, fn_args)
+                except Exception as e:
+                    result_text = f"Error: {e}"
+
+                tool_calls_log.append({
+                    "tool": fn_name,
+                    "arguments": fn_args,
+                    "result": result_text[:500],
+                })
+
+                messages.append({
+                    "role": "tool",
+                    "content": result_text,
+                    "tool_call_id": tc.id,
+                    "name": fn_name,
+                })
+
+        # Fallback if loop exhausted
+        return ChatResponse(answer="(max tool iterations reached)", tool_calls=tool_calls_log)
+
+
+# ---------------------------------------------------------------------------
+# FastAPI app
+# ---------------------------------------------------------------------------
+
+bridge = MCPBridge()
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    config_path = os.getenv("MCP_CONFIG", str(_PROJECT_ROOT / "config" / "server_config.json"))
+    await bridge.start(config_path)
+    yield
+    await bridge.stop()
+
+
+app = FastAPI(title="MCP HTTP Bridge", lifespan=lifespan)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+@app.get("/tools", response_model=List[ToolInfo])
+async def list_tools():
+    """List all available MCP tools."""
+    return bridge.tools
+
+
+@app.post("/chat", response_model=ChatResponse)
+async def chat(req: ChatRequest):
+    """Chat with LLM + MCP tools."""
+    try:
+        return await bridge.chat(req.query, req.history)
+    except ValueError as e:
+        raise HTTPException(status_code=503, detail=str(e))
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/tool", response_model=ToolCallResponse)
+async def call_tool(req: ToolCallRequest):
+    """Directly call an MCP tool."""
+    try:
+        result = await bridge.call_tool(req.tool, req.arguments)
+        return ToolCallResponse(result=result)
+    except ValueError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+    except Exception as e:
+        return ToolCallResponse(result=str(e), is_error=True)
+
+
+@app.get("/health")
+async def health():
+    return {
+        "status": "ok",
+        "servers": len(bridge.sessions),
+        "tools": len(bridge.tools),
+    }
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    port = int(os.getenv("MCP_BRIDGE_PORT", "8100"))
+    uvicorn.run(app, host="0.0.0.0", port=port)
diff --git a/pyproject.toml b/pyproject.toml
index f7b1903..cd7458f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,10 +5,14 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
+    "anthropic>=0.40.0",
+    "fastapi>=0.115.0",
+    "httpx>=0.27.0",
     "mcp[cli]>=1.6.0",
     "openai>=1.74.0",
     "python-dotenv>=1.1.0",
     "requests>=2.32.3",
     "tzdata>=2025.2",
     "ujson>=5.10.0",
+    "uvicorn>=0.32.0",
 ]
diff --git a/services/calculator_service.py b/services/calculator_service.py
new file mode 100644
index 0000000..6a0a9eb
--- /dev/null
+++ b/services/calculator_service.py
@@ -0,0 +1,123 @@
+"""Calculator MCP Service - performs math operations.
+
+No external API keys required. Works out of the box.
+"""
+import math
+from typing import Optional
+from mcp.server.fastmcp import FastMCP
+
+mcp = FastMCP("Calculator")
+
+
+@mcp.tool()
+async def calculate(expression: str) -> str:
+    """Evaluate a mathematical expression.
+
+    Supports basic arithmetic (+, -, *, /, **), math functions
+    (sqrt, sin, cos, tan, log, log10, abs, ceil, floor, pi, e),
+    and parentheses for grouping.
+
+    Args:
+        expression: A mathematical expression to evaluate, e.g. "2 + 3 * 4"
+    """
+    # Whitelist of safe names for eval
+    safe_names = {
+        "sqrt": math.sqrt,
+        "sin": math.sin,
+        "cos": math.cos,
+        "tan": math.tan,
+        "log": math.log,
+        "log10": math.log10,
+        "log2": math.log2,
+        "abs": abs,
+        "ceil": math.ceil,
+        "floor": math.floor,
+        "pow": pow,
+        "round": round,
+        "pi": math.pi,
+        "e": math.e,
+        "inf": math.inf,
+    }
+
+    try:
+        # Sanitize: only allow digits, operators, parens, dots, spaces, and function names
+        cleaned = expression.strip()
+
+        # Evaluate in restricted namespace
+        result = eval(cleaned, {"__builtins__": {}}, safe_names)  # noqa: S307
+        return f"{expression} = {result}"
+    except ZeroDivisionError:
+        return "Error: Division by zero"
+    except Exception as e:
+        return f"Error evaluating '{expression}': {str(e)}"
+
+
+@mcp.tool()
+async def unit_convert(value: float, from_unit: str, to_unit: str) -> str:
+    """Convert between common units.
+
+    Supported conversions:
+    - Temperature: celsius, fahrenheit, kelvin
+    - Length: meters, feet, inches, cm, km, miles
+    - Weight: kg, lbs, oz, grams
+
+    Args:
+        value: The numeric value to convert
+        from_unit: Source unit (e.g. "celsius", "meters", "kg")
+        to_unit: Target unit (e.g. "fahrenheit", "feet", "lbs")
+    """
+    from_unit = from_unit.lower().strip()
+    to_unit = to_unit.lower().strip()
+
+    # Temperature conversions
+    temp_conversions = {
+        ("celsius", "fahrenheit"): lambda v: v * 9 / 5 + 32,
+        ("fahrenheit", "celsius"): lambda v: (v - 32) * 5 / 9,
+        ("celsius", "kelvin"): lambda v: v + 273.15,
+        ("kelvin", "celsius"): lambda v: v - 273.15,
+        ("fahrenheit", "kelvin"): lambda v: (v - 32) * 5 / 9 + 273.15,
+        ("kelvin", "fahrenheit"): lambda v: (v - 273.15) * 9 / 5 + 32,
+    }
+
+    # Length conversions (to meters as base)
+    length_to_meters = {
+        "meters": 1.0, "m": 1.0,
+        "feet": 0.3048, "ft": 0.3048,
+        "inches": 0.0254, "in": 0.0254,
+        "cm": 0.01, "centimeters": 0.01,
+        "km": 1000.0, "kilometers": 1000.0,
+        "miles": 1609.344, "mi": 1609.344,
+        "yards": 0.9144, "yd": 0.9144,
+    }
+
+    # Weight conversions (to kg as base)
+    weight_to_kg = {
+        "kg": 1.0, "kilograms": 1.0,
+        "lbs": 0.453592, "pounds": 0.453592,
+        "oz": 0.0283495, "ounces": 0.0283495,
+        "grams": 0.001, "g": 0.001,
+    }
+
+    # Check temperature
+    key = (from_unit, to_unit)
+    if key in temp_conversions:
+        result = temp_conversions[key](value)
+        return f"{value} {from_unit} = {result:.4f} {to_unit}"
+
+    # Check length
+    if from_unit in length_to_meters and to_unit in length_to_meters:
+        meters = value * length_to_meters[from_unit]
+        result = meters / length_to_meters[to_unit]
+        return f"{value} {from_unit} = {result:.4f} {to_unit}"
+
+    # Check weight
+    if from_unit in weight_to_kg and to_unit in weight_to_kg:
+        kg = value * weight_to_kg[from_unit]
+        result = kg / weight_to_kg[to_unit]
+        return f"{value} {from_unit} = {result:.4f} {to_unit}"
+
+    return f"Error: Cannot convert from '{from_unit}' to '{to_unit}'. Supported: temperature (celsius/fahrenheit/kelvin), length (meters/feet/inches/cm/km/miles), weight (kg/lbs/oz/grams)"
+
+
+if __name__ == "__main__":
+    mcp.run(transport='stdio')
diff --git a/services/devops_knowledge_service.py b/services/devops_knowledge_service.py
new file mode 100644
index 0000000..321dd55
--- /dev/null
+++ b/services/devops_knowledge_service.py
@@ -0,0 +1,294 @@
+#!/usr/bin/env python3
+"""DevOps & LLM Interview Knowledge MCP Service.
+
+Serves interview Q&A from RAG datasets as MCP tools.
+Loads JSON datasets and provides search/browse/quiz capabilities.
+
+Datasets:
+  - devops_rag_answered_full_405_regenerated.json  (DevOps: 405 Q&A)
+  - llm_interview_note_qa.json                     (LLM: 405 Q&A)
+
+Usage:
+    python services/devops_knowledge_service.py
+    # Then connect via anthropic_mcp_client.py
+"""
+
+import json
+import random
+from pathlib import Path
+from typing import Optional
+
+from mcp.server.fastmcp import FastMCP
+
+mcp = FastMCP("DevOpsKnowledge")
+
+# ---------------------------------------------------------------------------
+# Data loading
+# ---------------------------------------------------------------------------
+RAG_DATA_DIR = Path(__file__).resolve().parent.parent / "data"
+_datasets: dict[str, list[dict]] = {}
+
+
+def _load_datasets():
+    """Load JSON datasets lazily on first use."""
+    if _datasets:
+        return
+
+    # Try multiple locations for the data files
+    search_dirs = [
+        RAG_DATA_DIR,
+        Path.home() / "dev" / "RAG" / "kubernetes_rag" / "data" / "devops_rag_kb",
+        Path.home() / "dev" / "devops-interview-questions" / "data",
+    ]
+
+    devops_files = [
+        "devops_rag_answered_full_405_regenerated.json",
+        "devops_rag_answered_full_405.json",
+    ]
+    llm_files = [
+        "llm_interview_note_qa.json",
+        "llm_interview_note_qa.jsonl",  # fallback when .json not present
+    ]
+
+    for search_dir in search_dirs:
+        if not search_dir.exists():
+            continue
+        for fname in devops_files:
+            p = search_dir / fname
+            if p.exists() and "devops" not in _datasets:
+                with open(p, encoding="utf-8") as f:
+                    _datasets["devops"] = json.load(f)
+                break
+        for fname in llm_files:
+            p = search_dir / fname
+            if p.exists() and "llm" not in _datasets:
+                with open(p, encoding="utf-8") as f:
+                    if fname.endswith(".jsonl"):
+                        _datasets["llm"] = [
+                            json.loads(line) for line in f if line.strip()
+                        ]
+                    else:
+                        _datasets["llm"] = json.load(f)
+                break
+
+    # If still not found, create a bundled fallback directory
+    if not _datasets:
+        RAG_DATA_DIR.mkdir(parents=True, exist_ok=True)
+
+
+def _get_all_entries(domain: Optional[str] = None) -> list[dict]:
+    """Get entries, optionally filtered by domain (devops/llm/all)."""
+    _load_datasets()
+    if domain and domain in _datasets:
+        return _datasets[domain]
+    entries = []
+    for ds in _datasets.values():
+        entries.extend(ds)
+    return entries
+
+
+def _get_categories(domain: Optional[str] = None) -> dict[str, int]:
+    """Get category counts."""
+    cats: dict[str, int] = {}
+    for e in _get_all_entries(domain):
+        c = e.get("category", "unknown")
+        cats[c] = cats.get(c, 0) + 1
+    return dict(sorted(cats.items(), key=lambda x: -x[1]))
+
+
+def _format_qa(entry: dict, detailed: bool = False) -> str:
+    """Format a Q&A entry for display."""
+    q = entry.get("question_zh") or entry.get("question", "")
+    cat = entry.get("category", "")
+    eid = entry.get("id", "")
+
+    parts = [f"[{eid}] ({cat})"]
+    parts.append(f"Q: {q}")
+
+    if detailed:
+        short = entry.get("short_answer_zh") or entry.get("answer", "")
+        detail = entry.get("detailed_answer_zh", "")
+        kp = entry.get("key_points_zh", [])
+
+        if short:
+            parts.append(f"\nShort Answer: {short}")
+        if detail:
+            parts.append(f"\nDetailed Answer: {detail[:1500]}")
+        if kp:
+            parts.append("\nKey Points:")
+            for p in kp:
+                parts.append(f"  - {p}")
+    else:
+        short = entry.get("short_answer_zh") or entry.get("answer", "")
+        if short:
+            parts.append(f"A: {short[:300]}")
+
+    return "\n".join(parts)
+
+
+# ---------------------------------------------------------------------------
+# MCP Tools
+# ---------------------------------------------------------------------------
+
+@mcp.tool()
+async def list_categories(domain: Optional[str] = None) -> str:
+    """List available Q&A categories with counts.
+
+    Args:
+        domain: Filter by domain - 'devops', 'llm', or None for all.
+    """
+    cats = _get_categories(domain)
+    total = sum(cats.values())
+    lines = [f"Total: {total} questions across {len(cats)} categories\n"]
+    for cat, count in cats.items():
+        lines.append(f"  {cat:30s} {count:4d}")
+    return "\n".join(lines)
+
+
+@mcp.tool()
+async def search_questions(
+    query: str,
+    domain: Optional[str] = None,
+    max_results: int = 5,
+) -> str:
+    """Search interview questions by keyword.
+
+    Args:
+        query: Search term (matches question text, category, keywords).
+        domain: Filter by 'devops', 'llm', or None for all.
+        max_results: Maximum results to return (default 5).
+    """
+    query_lower = query.lower()
+    entries = _get_all_entries(domain)
+
+    scored = []
+    for e in entries:
+        q = (e.get("question_zh") or e.get("question", "")).lower()
+        cat = e.get("category", "").lower()
+        kw = " ".join(e.get("keywords", [])).lower()
+        answer = (e.get("short_answer_zh") or e.get("answer", "")).lower()
+
+        score = 0
+        if query_lower in q:
+            score += 10
+        if query_lower in cat:
+            score += 5
+        if query_lower in kw:
+            score += 3
+        if query_lower in answer:
+            score += 1
+
+        if score > 0:
+            scored.append((score, e))
+
+    scored.sort(key=lambda x: -x[0])
+    results = scored[:max_results]
+
+    if not results:
+        return f"No results for '{query}'. Try broader terms or list_categories() first."
+
+    lines = [f"Found {len(scored)} matches for '{query}' (showing top {len(results)}):\n"]
+    for _, entry in results:
+        lines.append(_format_qa(entry, detailed=False))
+        lines.append("")
+    return "\n".join(lines)
+
+
+@mcp.tool()
+async def get_question_detail(question_id: str) -> str:
+    """Get full detailed answer for a specific question by ID.
+
+    Args:
+        question_id: The question ID (e.g., 'devops_001', 'llm_0042').
+    """
+    for entries in _datasets.values():
+        for e in entries:
+            if e.get("id") == question_id:
+                return _format_qa(e, detailed=True)
+    return f"Question '{question_id}' not found."
+
+
+@mcp.tool()
+async def get_questions_by_category(
+    category: str,
+    domain: Optional[str] = None,
+    max_results: int = 10,
+) -> str:
+    """Get questions from a specific category.
+
+    Args:
+        category: Category name (e.g., 'kubernetes', 'llm_architecture', 'jenkins').
+        domain: Filter by 'devops', 'llm', or None for all.
+        max_results: Maximum results (default 10).
+    """
+    entries = _get_all_entries(domain)
+    cat_lower = category.lower()
+    matches = [e for e in entries if cat_lower in e.get("category", "").lower()]
+
+    if not matches:
+        cats = _get_categories(domain)
+        return f"Category '{category}' not found. Available: {', '.join(cats.keys())}"
+
+    lines = [f"Category '{category}': {len(matches)} questions (showing {min(len(matches), max_results)}):\n"]
+    for e in matches[:max_results]:
+        lines.append(_format_qa(e, detailed=False))
+        lines.append("")
+    return "\n".join(lines)
+
+
+@mcp.tool()
+async def quiz_me(
+    category: Optional[str] = None,
+    domain: Optional[str] = None,
+    count: int = 3,
+) -> str:
+    """Generate a random quiz from the knowledge base.
+
+    Args:
+        category: Optional category filter.
+        domain: Filter by 'devops', 'llm', or None for all.
+        count: Number of questions (default 3).
+    """
+    entries = _get_all_entries(domain)
+    if category:
+        cat_lower = category.lower()
+        entries = [e for e in entries if cat_lower in e.get("category", "").lower()]
+
+    if not entries:
+        return "No questions available for the given filters."
+
+    selected = random.sample(entries, min(count, len(entries)))
+    lines = [f"Quiz ({len(selected)} questions):\n"]
+    for i, e in enumerate(selected, 1):
+        q = e.get("question_zh") or e.get("question", "")
+        eid = e.get("id", "")
+        cat = e.get("category", "")
+        lines.append(f"{i}. [{eid}] ({cat}) {q}")
+    lines.append(f"\nUse get_question_detail(id) to see the answer for each question.")
+    return "\n".join(lines)
+
+
+@mcp.tool()
+async def dataset_stats() -> str:
+    """Get statistics about loaded datasets."""
+    _load_datasets()
+    lines = ["Dataset Statistics:\n"]
+    total = 0
+    for name, entries in _datasets.items():
+        cats = {}
+        for e in entries:
+            c = e.get("category", "unknown")
+            cats[c] = cats.get(c, 0) + 1
+        lines.append(f"  {name}: {len(entries)} entries, {len(cats)} categories")
+        total += len(entries)
+    lines.append(f"\n  Total: {total} Q&A pairs")
+
+    all_cats = _get_categories()
+    lines.append(f"\nAll categories ({len(all_cats)}):")
+    for cat, count in all_cats.items():
+        lines.append(f"  {cat:30s} {count:4d}")
+    return "\n".join(lines)
+
+
+if __name__ == "__main__":
+    mcp.run(transport="stdio")
diff --git a/services/res_prompt_services.py b/services/res_prompt_services.py
index 73f9f19..867b34e 100644
--- a/services/res_prompt_services.py
+++ b/services/res_prompt_services.py
@@ -5,13 +5,10 @@
 """
 
 from datetime import datetime
-import glob
 import json
 import os
-from typing import List
-from mcp import Resource
+
 from mcp.server.fastmcp import FastMCP
-from mcp.types import Resource, TextContent, EmbeddedResource
 
 
 # 初始化 FastMCP 服务器
diff --git a/services/time_service.py b/services/time_service.py
index 32ea90d..22de348 100644
--- a/services/time_service.py
+++ b/services/time_service.py
@@ -21,8 +21,11 @@ async def get_current_time(timezone: Optional[str] = None) -> str:
     try:
         # 输入清理和规范化
         if timezone:
-            # 去除前后空格并替换下划线为斜杠（处理常见笔误）
-            cleaned_tz = timezone.strip().replace("_", "/")
+            cleaned_tz = timezone.strip()
+            # Only convert underscore to slash if no slash present
+            # (handles input like "Asia_Shanghai" but preserves "America/New_York")
+            if "/" not in cleaned_tz:
+                cleaned_tz = cleaned_tz.replace("_", "/")
             tz = ZoneInfo(cleaned_tz)
         else:
             tz = datetime.now().astimezone().tzinfo
diff --git a/simple_mcp_client.py b/simple_mcp_client.py
index be1e52b..0271c01 100644
--- a/simple_mcp_client.py
+++ b/simple_mcp_client.py
@@ -3,6 +3,7 @@
 import sys
 import json
 from contextlib import AsyncExitStack
+from pathlib import Path
 from typing import Optional, List, Dict, Any
 
 from mcp import ClientSession, StdioServerParameters
@@ -10,7 +11,8 @@
 from openai import AsyncOpenAI
 from dotenv import load_dotenv
 
-load_dotenv()
+_PROJECT_ROOT = Path(__file__).resolve().parent
+load_dotenv(dotenv_path=_PROJECT_ROOT / ".env", override=True)
 
 class MCPClient:
     def __init__(
@@ -149,7 +151,7 @@ async def connect_to_server(self, server_params: StdioServerParameters):
         # print(f"[SYS]: 可用 Prompt: {prompts_names}")
         print(f"[SYS]: 可用 Prompt: {self.prompts_dict}")
 
-    async def selcect_prompt_template(self, user_question: str) -> str:
+    async def select_prompt_template(self, user_question: str) -> str:
         """ 根据用户问题选择 prompt 模板
         """
         # 需要详细回答的指示词
@@ -217,7 +219,7 @@ async def process_query(self, query: str) -> str:
         user_text = query.strip()
         # 1.选择 prompt
         if self.prompts_dict:
-            template_name = await self.selcect_prompt_template(user_text)
+            template_name = await self.select_prompt_template(user_text)
             prompt_response = await self.session.get_prompt(
                 template_name, arguments={"question": user_text}
             )
@@ -324,7 +326,7 @@ async def cleanup(self):
             try:
                 await self.exit_stack.aclose()
                 self.session = None
-                self.stdio_context = None
+                self.stdio_transport = None
             except Exception as e:
                 print(f"Error during cleanup of server: {e}")
 
diff --git a/simple_mcp_client_stream.py b/simple_mcp_client_stream.py
index b27c34f..2fc441f 100644
--- a/simple_mcp_client_stream.py
+++ b/simple_mcp_client_stream.py
@@ -1,20 +1,18 @@
 import asyncio
-import re
 import os
 import sys
 import json
 from contextlib import AsyncExitStack
+from pathlib import Path
 from typing import Optional, List, Dict, Any
 
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
 from openai import AsyncOpenAI
-from dotenv import load_dotenv, dotenv_values
+from dotenv import load_dotenv
 
-load_dotenv(
-    dotenv_path=".env", 
-    override=True
-)
+_PROJECT_ROOT = Path(__file__).resolve().parent
+load_dotenv(dotenv_path=_PROJECT_ROOT / ".env", override=True)
 
 class MCPClient:
     def __init__(
@@ -132,7 +130,7 @@ async def connect_to_server(self, server_params: StdioServerParameters):
         # print(f"[SYS]: 可用 Prompt: {prompts_names}")
         print(f"[SYS]: 可用 Prompt: {self.prompts_dict}")
 
-    async def selcect_prompt_template(self, user_question: str) -> str:
+    async def select_prompt_template(self, user_question: str) -> str:
         """ 根据用户问题选择 prompt 模板
         """
         # 需要详细回答的指示词
@@ -207,7 +205,7 @@ async def process_query(self, query: str, messages: List[dict] = None, depth: in
             user_text = query.strip()
             # 1.选择 prompt
             if self.prompts_dict:
-                template_name = await self.selcect_prompt_template(user_text)
+                template_name = await self.select_prompt_template(user_text)
                 prompt_response = await self.session.get_prompt(
                     template_name, 
                     arguments={"question": user_text}
@@ -357,7 +355,7 @@ async def cleanup(self):
             try:
                 await self.exit_stack.aclose()
                 self.session = None
-                self.stdio_context = None
+                self.stdio_transport = None
             except Exception as e:
                 print(f"Error during cleanup of server: {e}")
 
diff --git a/test_services.py b/test_services.py
new file mode 100644
index 0000000..4a159f1
--- /dev/null
+++ b/test_services.py
@@ -0,0 +1,102 @@
+#!/usr/bin/env python3
+"""Test all MCP services end-to-end without needing an LLM API key.
+
+Usage:
+    source .venv/bin/activate
+    python test_services.py
+"""
+import asyncio
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+from contextlib import AsyncExitStack
+
+
+async def test_service(name: str, script: str, tool_name: str, tool_args: dict):
+    """Connect to an MCP service, list tools, and call one tool."""
+    print(f"\n{'='*60}")
+    print(f"Testing: {name} ({script})")
+    print(f"{'='*60}")
+
+    import os
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+    venv_python = os.path.join(base_dir, ".venv", "bin", "python")
+    if not os.path.exists(venv_python):
+        venv_python = "python"  # fallback
+
+    exit_stack = AsyncExitStack()
+    try:
+        server_params = StdioServerParameters(
+            command=venv_python,
+            args=[os.path.join(base_dir, "services", script)],
+            env=None
+        )
+
+        stdio_transport = await exit_stack.enter_async_context(
+            stdio_client(server_params)
+        )
+        reader, writer = stdio_transport
+
+        session = await exit_stack.enter_async_context(
+            ClientSession(reader, writer)
+        )
+        await session.initialize()
+
+        # List tools
+        tools_response = await session.list_tools()
+        tool_names = [t.name for t in tools_response.tools]
+        print(f"  Connected! Available tools: {tool_names}")
+
+        for tool in tools_response.tools:
+            print(f"    - {tool.name}: {tool.description}")
+
+        # Call tool
+        print(f"\n  Calling: {tool_name}({tool_args})")
+        result = await session.call_tool(tool_name, tool_args)
+        print(f"  Result: {result.content[0].text}")
+        print(f"\n  ✓ PASS")
+
+    except Exception as e:
+        print(f"\n  ✗ FAIL: {e}")
+    finally:
+        await exit_stack.aclose()
+
+
+async def main():
+    print("tiny-mcp Service Test Suite")
+    print("=" * 60)
+
+    await test_service(
+        name="Time Service",
+        script="time_service.py",
+        tool_name="get_current_time",
+        tool_args={"timezone": "America/New_York"},
+    )
+
+    await test_service(
+        name="Calculator Service",
+        script="calculator_service.py",
+        tool_name="calculate",
+        tool_args={"expression": "sqrt(144) + 3 ** 2"},
+    )
+
+    await test_service(
+        name="Calculator - Unit Conversion",
+        script="calculator_service.py",
+        tool_name="unit_convert",
+        tool_args={"value": 72.0, "from_unit": "fahrenheit", "to_unit": "celsius"},
+    )
+
+    await test_service(
+        name="US Weather Service",
+        script="weather_service_us.py",
+        tool_name="get_alerts",
+        tool_args={"state": "CA"},
+    )
+
+    print(f"\n{'='*60}")
+    print("All tests completed!")
+    print(f"{'='*60}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/tiny-mcp b/tiny-mcp
new file mode 160000
index 0000000..215613a
--- /dev/null
+++ b/tiny-mcp
@@ -0,0 +1 @@
+Subproject commit 215613ab35848607e98092680fcb714eacb861e0
diff --git a/uv.lock b/uv.lock
index 64e4175..b2ace5c 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,14 +1,33 @@
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-revision = 1
+revision = 3
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+]
+
+[[package]]
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+version = "0.84.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "docstring-parser" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/04/ea/0869d6df9ef83dcf393aeefc12dd81677d091c6ffc86f783e51cf44062f2/anthropic-0.84.0.tar.gz", hash = "sha256:72f5f90e5aebe62dca316cb013629cfa24996b0f5a4593b8c3d712bc03c43c37", size = 539457, upload-time = "2026-02-25T05:22:38.54Z" }
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