Revamped quickstart again
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Zachary Lee
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tutorials/building-a-client.mdx
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tutorials/building-a-client.mdx
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---
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title: "Building a MCP client"
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description: "Learn how to build your first client in MCP"
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---
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In this tutorial, you'll learn how to build a client application that connects to MCP servers.
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## Prerequisite Knowledge
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This tutorial assumes familiarity with:
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- Python
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- LLMs like Claude
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It helps to understand [tool use (aka function calling)](https://docs.anthropic.com/en/docs/build-with-claude/tool-use), but it's not required.
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## System Requirements
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Before starting, ensure your system meets these requirements:
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- Mac or Windows computer
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- Latest Python version installed
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## Setting Up Your Environment
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First, create and activate a virtual environment:
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```bash
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# Install virtualenv if needed
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pip install virtualenv
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# Create project directory
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mkdir mcp-client
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cd mcp-client
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# Create virtual environment
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python -m virtualenv venv
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# Activate virtual environment
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# On Windows:
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venv\Scripts\activate
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# On Unix or MacOS:
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source venv/bin/activate
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# Install required packages
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pip install mcp anthropic python-dotenv
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```
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## Setting Up Your API Key
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You'll need an Anthropic API key from the [Anthropic Console](https://console.anthropic.com/settings/keys).
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Create a `.env` file to store it:
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```bash
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# Create .env file
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touch .env
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```
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Add your key to the `.env` file:
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```bash
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ANTHROPIC_API_KEY=<your key here>
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```
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Add `.env` to your `.gitignore`:
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```bash
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echo ".env" >> .gitignore
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```
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## Creating the Client
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Let's create a Python client that can connect to any MCP server. We'll call it `client.py`:
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```python
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import asyncio
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from typing import Optional
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from contextlib import AsyncExitStack
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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from anthropic import Anthropic
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from dotenv import load_dotenv
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load_dotenv() # load environment variables from .env
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class MCPClient:
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def __init__(self):
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# Initialize session and client objects
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self.session: Optional[ClientSession] = None
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self.exit_stack = AsyncExitStack()
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self.anthropic = Anthropic()
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async def connect_to_server(self, server_script_path: str):
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"""Connect to an MCP server"""
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server_params = StdioServerParameters(
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command="python",
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args=[server_script_path],
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env=None
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)
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stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
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self.stdio, self.write = stdio_transport
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self.session = await self.exit_stack.enter_async_context(ClientSession(self.stdio, self.write))
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await self.session.initialize()
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# List available tools
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response = await self.session.list_tools()
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tools = response.tools
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print("\nConnected to server with tools:", [tool.name for tool in tools])
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async def process_query(self, query: str) -> str:
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"""Process a query using Claude and available tools"""
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messages = [
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{
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"role": "user",
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"content": query
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}
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]
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response = await self.session.list_tools()
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available_tools = [{
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"name": tool.name,
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"description": tool.description,
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"input_schema": tool.inputSchema
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} for tool in response.tools]
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# Initial Claude API call
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response = self.anthropic.messages.create(
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model="claude-3-5-sonnet-20241022",
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max_tokens=1000,
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messages=messages,
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tools=available_tools
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)
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# Process response and handle tool calls
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tool_results = []
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final_text = []
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for content in response.content:
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if content.type == 'text':
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final_text.append(content.text)
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elif content.type == 'tool_use':
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tool_name = content.name
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tool_args = content.input
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# Execute tool call
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result = await self.session.call_tool(tool_name, tool_args)
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tool_results.append({"call": tool_name, "result": result})
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final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")
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# Continue conversation with tool results
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if hasattr(content, 'text') and content.text:
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messages.append({
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"role": "assistant",
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"content": content.text
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})
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messages.append({
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"role": "user",
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"content": result.content
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})
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# Get next response from Claude
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response = self.anthropic.messages.create(
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model="claude-3-5-sonnet-20241022",
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max_tokens=1000,
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messages=messages,
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)
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final_text.append(response.content[0].text)
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return "\n".join(final_text)
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async def chat_loop(self):
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"""Run an interactive chat loop"""
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print("\nMCP Client Started!")
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print("Type your queries or 'quit' to exit.")
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while True:
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try:
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query = input("\nQuery: ").strip()
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if query.lower() == 'quit':
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break
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response = await self.process_query(query)
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print("\n" + response)
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except Exception as e:
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print(f"\nError: {str(e)}")
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async def cleanup(self):
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"""Clean up resources"""
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await self.exit_stack.aclose()
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async def main():
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if len(sys.argv) < 2:
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print("Usage: python client.py <path_to_server_script>")
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sys.exit(1)
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client = MCPClient()
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try:
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await client.connect_to_server(sys.argv[1])
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await client.chat_loop()
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finally:
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await client.cleanup()
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if __name__ == "__main__":
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import sys
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asyncio.run(main())
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```
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## Understanding the Client Code
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Let's break down the key components of our MCP client:
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1. **MCPClient Class**
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- Manages the connection to the MCP server
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- Handles communication between Claude and the server's tools
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- Maintains the chat session
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2. **Key Methods**
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- `connect_to_server()`: Establishes connection with an MCP server
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- `process_query()`: Handles user queries by:
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- Getting available tools from the server
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- Sending the query to Claude with tool information
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- Executing any tool calls Claude requests
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- Processing Claude's responses
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- `chat_loop()`: Runs the interactive chat interface
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- `cleanup()`: Properly closes connections and resources
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## Running the Client
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To run your client with any MCP server:
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```bash
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python client.py path/to/server.py
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```
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The client will:
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1. Connect to the specified server
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2. List available tools
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3. Start an interactive chat session where you can:
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- Enter queries
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- See tool executions
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- Get responses from Claude
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## How It Works
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When you submit a query:
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1. The client gets the list of available tools from the server
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2. Your query is sent to Claude along with tool descriptions
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3. Claude decides which tools (if any) to use
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4. The client executes any requested tool calls through the server
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5. Results are sent back to Claude
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6. Claude provides a natural language response
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7. The response is displayed to you
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## Best Practices
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1. **Error Handling**
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- Always wrap tool calls in try-catch blocks
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- Provide meaningful error messages
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- Gracefully handle connection issues
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2. **Resource Management**
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- Use `AsyncExitStack` for proper cleanup
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- Close connections when done
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- Handle server disconnections
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3. **Security**
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- Store API keys securely in `.env`
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- Validate server responses
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- Be cautious with tool permissions
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## Next Steps
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Now that you have a basic MCP client, you can:
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1. Add support for different server types
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2. Enhance error handling and recovery
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3. Implement more sophisticated conversation handling
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4. Add authentication and security features
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5. Create a better user interface
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## Resources
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- [MCP Documentation](https://modelcontextprotocol.github.io/)
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- [Claude API Documentation](https://docs.anthropic.com/claude/reference)
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- [Tool Use Guide](https://docs.anthropic.com/claude/docs/function-calling)
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