Create Python implementation of MCP client prototype
Jaronim Pracht
parent
89bbc68c2a
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.env
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__pycache__
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.venv
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.roproject
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3.13
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import asyncio
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import json
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import logging
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import os
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import shutil
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from contextlib import AsyncExitStack
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from typing import Any
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from openai import AzureOpenAI
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import httpx
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from dotenv import load_dotenv
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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# Configure logging
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logging.basicConfig(
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level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
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)
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class Configuration:
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"""Manages configuration and environment variables for the MCP client."""
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def __init__(self) -> None:
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"""Initialize configuration with environment variables."""
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self.load_env()
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self.api_key = os.getenv("LLM_API_KEY")
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@staticmethod
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def load_env() -> None:
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"""Load environment variables from .env file."""
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load_dotenv()
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@staticmethod
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def load_config(file_path: str) -> dict[str, Any]:
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"""Load server configuration from JSON file.
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Args:
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file_path: Path to the JSON configuration file.
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Returns:
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Dict containing server configuration.
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Raises:
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FileNotFoundError: If configuration file doesn't exist.
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JSONDecodeError: If configuration file is invalid JSON.
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"""
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with open(file_path, "r") as f:
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return json.load(f)
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@property
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def llm_api_key(self) -> str:
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"""Get the LLM API key.
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Returns:
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The API key as a string.
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Raises:
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ValueError: If the API key is not found in environment variables.
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"""
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if not self.api_key:
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raise ValueError("LLM_API_KEY not found in environment variables")
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return self.api_key
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class Server:
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"""Manages MCP server connections and tool execution."""
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def __init__(self, name: str, config: dict[str, Any]) -> None:
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self.name: str = name
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self.config: dict[str, Any] = config
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self.stdio_context: Any | None = None
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self.session: ClientSession | None = None
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self._cleanup_lock: asyncio.Lock = asyncio.Lock()
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self.exit_stack: AsyncExitStack = AsyncExitStack()
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async def initialize(self) -> None:
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"""Initialize the server connection."""
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command = (
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shutil.which("npx")
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if self.config["command"] == "npx"
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else self.config["command"]
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)
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if command is None:
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raise ValueError("The command must be a valid string and cannot be None.")
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server_params = StdioServerParameters(
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command=command,
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args=self.config["args"],
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env={**os.environ, **self.config["env"]}
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if self.config.get("env")
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else None,
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)
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try:
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stdio_transport = await self.exit_stack.enter_async_context(
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stdio_client(server_params)
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)
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read, write = stdio_transport
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session = await self.exit_stack.enter_async_context(
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ClientSession(read, write)
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)
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await session.initialize()
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self.session = session
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except Exception as e:
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logging.error(f"Error initializing server {self.name}: {e}")
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await self.cleanup()
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raise
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async def list_tools(self) -> list[Any]:
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"""List available tools from the server.
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Returns:
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A list of available tools.
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Raises:
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RuntimeError: If the server is not initialized.
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"""
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if not self.session:
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raise RuntimeError(f"Server {self.name} not initialized")
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tools_response = await self.session.list_tools()
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tools = []
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for item in tools_response:
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if isinstance(item, tuple) and item[0] == "tools":
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tools.extend(
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Tool(tool.name, tool.description, tool.inputSchema)
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for tool in item[1]
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)
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return tools
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async def execute_tool(
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self,
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tool_name: str,
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arguments: dict[str, Any],
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retries: int = 2,
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delay: float = 1.0,
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) -> Any:
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"""Execute a tool with retry mechanism.
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Args:
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tool_name: Name of the tool to execute.
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arguments: Tool arguments.
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retries: Number of retry attempts.
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delay: Delay between retries in seconds.
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Returns:
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Tool execution result.
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Raises:
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RuntimeError: If server is not initialized.
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Exception: If tool execution fails after all retries.
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"""
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if not self.session:
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raise RuntimeError(f"Server {self.name} not initialized")
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attempt = 0
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while attempt < retries:
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try:
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logging.info(f"Executing {tool_name}...")
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result = await self.session.call_tool(tool_name, arguments)
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return result
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except Exception as e:
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attempt += 1
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logging.warning(
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f"Error executing tool: {e}. Attempt {attempt} of {retries}."
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)
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if attempt < retries:
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logging.info(f"Retrying in {delay} seconds...")
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await asyncio.sleep(delay)
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else:
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logging.error("Max retries reached. Failing.")
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raise
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async def cleanup(self) -> None:
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"""Clean up server resources."""
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async with self._cleanup_lock:
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try:
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await self.exit_stack.aclose()
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self.session = None
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self.stdio_context = None
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except Exception as e:
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logging.error(f"Error during cleanup of server {self.name}: {e}")
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class Tool:
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"""Represents a tool with its properties and formatting."""
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def __init__(
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self, name: str, description: str, input_schema: dict[str, Any]
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) -> None:
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self.name: str = name
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self.description: str = description
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self.input_schema: dict[str, Any] = input_schema
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def format_for_llm(self) -> str:
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"""Format tool information for LLM.
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Returns:
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A formatted string describing the tool.
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"""
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args_desc = []
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if "properties" in self.input_schema:
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for param_name, param_info in self.input_schema["properties"].items():
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arg_desc = (
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f"- {param_name}: {param_info.get('description', 'No description')}"
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)
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if param_name in self.input_schema.get("required", []):
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arg_desc += " (required)"
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args_desc.append(arg_desc)
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return f"""
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Tool: {self.name}
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Description: {self.description}
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Arguments:
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{chr(10).join(args_desc)}
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"""
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class LLMClient:
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"""Manages communication with the LLM provider."""
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def __init__(self, api_key: str) -> None:
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self.api_key: str = api_key
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def get_response(self, messages: list[dict[str, str]]) -> str:
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"""Get a response from the LLM.
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Args:
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messages: A list of message dictionaries.
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Returns:
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The LLM's response as a string.
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Raises:
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httpx.RequestError: If the request to the LLM fails.
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"""
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url = "https://ai.exxeta.com/api/v2/azure/openai"
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# Convert messages to the correct format expected by the API
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formatted_messages = []
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for msg in messages:
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print(msg)
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formatted_messages.append({
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"role": msg["role"],
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"content": msg["content"]
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})
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client = AzureOpenAI(
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api_key=self.api_key,
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api_version="2023-07-01-preview",
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base_url=url
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)
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response = client.chat.completions.create(
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messages=formatted_messages,
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model="gpt-4o-mini",
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# response_format={"type": "json_object"}
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# temperature=0.7,
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# top_p=0.95,
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# frequency_penalty=0,
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# presence_penalty=0,
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# max_tokens=800,
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# stop="",
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# stream=False
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)
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if response.choices[0].message.content:
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print("response: " + response.choices[0].message.content)
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return response.choices[0].message.content
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print("No response from Azure OpenAI")
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# url = "https://api.groq.com/openai/v1/chat/completions"
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.api_key}",
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}
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payload = {
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"messages": messages,
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"model": "gpt-4o-mini",
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"temperature": 0.7,
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"max_tokens": 4096,
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"top_p": 1,
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"stream": False,
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"stop": None,
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}
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try:
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with httpx.Client() as client:
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response = client.post(url, headers=headers, json=payload)
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response.raise_for_status()
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data = response.json()
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return data["choices"][0]["message"]["content"]
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except httpx.RequestError as e:
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error_message = f"Error getting LLM response: {str(e)}"
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logging.error(error_message)
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if isinstance(e, httpx.HTTPStatusError):
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status_code = e.response.status_code
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logging.error(f"Status code: {status_code}")
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logging.error(f"Response details: {e.response.text}")
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return (
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f"I encountered an error: {error_message}. "
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"Please try again or rephrase your request."
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)
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class ChatSession:
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"""Orchestrates the interaction between user, LLM, and tools."""
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def __init__(self, servers: list[Server], llm_client: LLMClient) -> None:
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self.servers: list[Server] = servers
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self.llm_client: LLMClient = llm_client
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async def cleanup_servers(self) -> None:
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"""Clean up all servers properly."""
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cleanup_tasks = [
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asyncio.create_task(server.cleanup()) for server in self.servers
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]
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if cleanup_tasks:
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try:
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await asyncio.gather(*cleanup_tasks, return_exceptions=True)
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except Exception as e:
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logging.warning(f"Warning during final cleanup: {e}")
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async def process_llm_response(self, llm_response: str) -> str:
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"""Process the LLM response and execute tools if needed.
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Args:
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llm_response: The response from the LLM.
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Returns:
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The result of tool execution or the original response.
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"""
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import json
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try:
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tool_call = json.loads(llm_response)
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if "tool" in tool_call and "arguments" in tool_call:
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logging.info(f"Executing tool: {tool_call['tool']}")
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logging.info(f"With arguments: {tool_call['arguments']}")
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for server in self.servers:
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tools = await server.list_tools()
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if any(tool.name == tool_call["tool"] for tool in tools):
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try:
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result = await server.execute_tool(
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tool_call["tool"], tool_call["arguments"]
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)
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if isinstance(result, dict) and "progress" in result:
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progress = result["progress"]
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total = result["total"]
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percentage = (progress / total) * 100
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logging.info(
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f"Progress: {progress}/{total} "
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f"({percentage:.1f}%)"
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)
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return f"Tool execution result: {result}"
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except Exception as e:
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error_msg = f"Error executing tool: {str(e)}"
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logging.error(error_msg)
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return error_msg
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return f"No server found with tool: {tool_call['tool']}"
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return llm_response
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except json.JSONDecodeError:
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return llm_response
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async def start(self) -> None:
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"""Main chat session handler."""
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try:
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for server in self.servers:
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try:
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await server.initialize()
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except Exception as e:
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logging.error(f"Failed to initialize server: {e}")
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await self.cleanup_servers()
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return
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all_tools = []
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for server in self.servers:
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tools = await server.list_tools()
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all_tools.extend(tools)
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tools_description = "\n".join([tool.format_for_llm() for tool in all_tools])
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system_message = (
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"You are a helpful assistant with access to these tools:\n\n"
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f"{tools_description}\n"
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"Choose the appropriate tool based on the user's question. "
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"If no tool is needed, reply directly.\n\n"
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"IMPORTANT: When you need to use a tool, you must ONLY respond with "
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"the exact JSON object format below, nothing else:\n"
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"{\n"
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' "tool": "tool-name",\n'
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' "arguments": {\n'
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' "argument-name": "value"\n'
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" }\n"
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"}\n\n"
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"After receiving a tool's response:\n"
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"1. Transform the raw data into a natural, conversational response\n"
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"2. Keep responses concise but informative\n"
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"3. Focus on the most relevant information\n"
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||||||
|
"4. Use appropriate context from the user's question\n"
|
||||||
|
"5. Avoid simply repeating the raw data\n\n"
|
||||||
|
"Please use only the tools that are explicitly defined above."
|
||||||
|
)
|
||||||
|
|
||||||
|
messages = [{"role": "system", "content": system_message}]
|
||||||
|
|
||||||
|
while True:
|
||||||
|
try:
|
||||||
|
user_input = input("You: ").strip().lower()
|
||||||
|
if user_input in ["quit", "exit"]:
|
||||||
|
logging.info("\nExiting...")
|
||||||
|
break
|
||||||
|
|
||||||
|
messages.append({"role": "user", "content": user_input})
|
||||||
|
|
||||||
|
llm_response = self.llm_client.get_response(messages)
|
||||||
|
logging.info("\nAssistant: %s", llm_response)
|
||||||
|
|
||||||
|
result = await self.process_llm_response(llm_response)
|
||||||
|
|
||||||
|
if result != llm_response:
|
||||||
|
messages.append({"role": "assistant", "content": llm_response})
|
||||||
|
messages.append({"role": "system", "content": result})
|
||||||
|
|
||||||
|
final_response = self.llm_client.get_response(messages)
|
||||||
|
logging.info("\nFinal response: %s", final_response)
|
||||||
|
messages.append(
|
||||||
|
{"role": "assistant", "content": final_response}
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
messages.append({"role": "assistant", "content": llm_response})
|
||||||
|
|
||||||
|
except KeyboardInterrupt:
|
||||||
|
logging.info("\nExiting...")
|
||||||
|
break
|
||||||
|
|
||||||
|
finally:
|
||||||
|
await self.cleanup_servers()
|
||||||
|
|
||||||
|
|
||||||
|
async def main() -> None:
|
||||||
|
"""Initialize and run the chat session."""
|
||||||
|
config = Configuration()
|
||||||
|
server_config = config.load_config("servers_config.json")
|
||||||
|
servers = [
|
||||||
|
Server(name, srv_config)
|
||||||
|
for name, srv_config in server_config["mcpServers"].items()
|
||||||
|
]
|
||||||
|
llm_client = LLMClient(config.llm_api_key)
|
||||||
|
chat_session = ChatSession(servers, llm_client)
|
||||||
|
await chat_session.start()
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
asyncio.run(main())
|
||||||
|
|
@ -0,0 +1,18 @@
|
||||||
|
# server.py
|
||||||
|
from mcp.server.fastmcp import FastMCP
|
||||||
|
# Create an MCP server
|
||||||
|
mcp = FastMCP("Demo")
|
||||||
|
|
||||||
|
|
||||||
|
# Add an addition tool
|
||||||
|
@mcp.tool()
|
||||||
|
def add(a: int, b: int) -> int:
|
||||||
|
"""Add two numbers"""
|
||||||
|
return 42
|
||||||
|
|
||||||
|
|
||||||
|
# Add a dynamic greeting resource
|
||||||
|
@mcp.resource("greeting://{name}")
|
||||||
|
def get_greeting(name: str) -> str:
|
||||||
|
"""Get a personalized greeting"""
|
||||||
|
return f"Hello, {name}!"
|
||||||
|
|
@ -0,0 +1,10 @@
|
||||||
|
[project]
|
||||||
|
name = "first-mcp-python"
|
||||||
|
version = "0.1.0"
|
||||||
|
description = "Add your description here"
|
||||||
|
readme = "README.md"
|
||||||
|
requires-python = ">=3.13"
|
||||||
|
dependencies = [
|
||||||
|
"mcp[cli]>=1.6.0",
|
||||||
|
"openai>=1.76.0",
|
||||||
|
]
|
||||||
|
|
@ -0,0 +1,8 @@
|
||||||
|
{
|
||||||
|
"mcpServers": {
|
||||||
|
"sqlite": {
|
||||||
|
"command": "uv",
|
||||||
|
"args": ["run", "mcp", "run", "main.py"]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,414 @@
|
||||||
|
version = 1
|
||||||
|
revision = 2
|
||||||
|
requires-python = ">=3.13"
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "annotated-types"
|
||||||
|
version = "0.7.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload_time = "2024-05-20T21:33:25.928Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload_time = "2024-05-20T21:33:24.1Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "anyio"
|
||||||
|
version = "4.9.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
dependencies = [
|
||||||
|
{ name = "idna" },
|
||||||
|
{ name = "sniffio" },
|
||||||
|
]
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949, upload_time = "2025-03-17T00:02:54.77Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916, upload_time = "2025-03-17T00:02:52.713Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "certifi"
|
||||||
|
version = "2025.4.26"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/e8/9e/c05b3920a3b7d20d3d3310465f50348e5b3694f4f88c6daf736eef3024c4/certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6", size = 160705, upload_time = "2025-04-26T02:12:29.51Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/4a/7e/3db2bd1b1f9e95f7cddca6d6e75e2f2bd9f51b1246e546d88addca0106bd/certifi-2025.4.26-py3-none-any.whl", hash = "sha256:30350364dfe371162649852c63336a15c70c6510c2ad5015b21c2345311805f3", size = 159618, upload_time = "2025-04-26T02:12:27.662Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "click"
|
||||||
|
version = "8.1.8"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
dependencies = [
|
||||||
|
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||||
|
]
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593, upload_time = "2024-12-21T18:38:44.339Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/7e/d4/7ebdbd03970677812aac39c869717059dbb71a4cfc033ca6e5221787892c/click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2", size = 98188, upload_time = "2024-12-21T18:38:41.666Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "colorama"
|
||||||
|
version = "0.4.6"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload_time = "2022-10-25T02:36:22.414Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload_time = "2022-10-25T02:36:20.889Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "distro"
|
||||||
|
version = "1.9.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload_time = "2023-12-24T09:54:32.31Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload_time = "2023-12-24T09:54:30.421Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "first-mcp-python"
|
||||||
|
version = "0.1.0"
|
||||||
|
source = { virtual = "." }
|
||||||
|
dependencies = [
|
||||||
|
{ name = "mcp", extra = ["cli"] },
|
||||||
|
{ name = "openai" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.metadata]
|
||||||
|
requires-dist = [
|
||||||
|
{ name = "mcp", extras = ["cli"], specifier = ">=1.6.0" },
|
||||||
|
{ name = "openai", specifier = ">=1.76.0" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "h11"
|
||||||
|
version = "0.16.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload_time = "2025-04-24T03:35:25.427Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload_time = "2025-04-24T03:35:24.344Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "httpcore"
|
||||||
|
version = "1.0.9"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
dependencies = [
|
||||||
|
{ name = "certifi" },
|
||||||
|
{ name = "h11" },
|
||||||
|
]
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload_time = "2025-04-24T22:06:22.219Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload_time = "2025-04-24T22:06:20.566Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "httpx"
|
||||||
|
version = "0.28.1"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
dependencies = [
|
||||||
|
{ name = "anyio" },
|
||||||
|
{ name = "certifi" },
|
||||||
|
{ name = "httpcore" },
|
||||||
|
{ name = "idna" },
|
||||||
|
]
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload_time = "2024-12-06T15:37:23.222Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload_time = "2024-12-06T15:37:21.509Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "httpx-sse"
|
||||||
|
version = "0.4.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/4c/60/8f4281fa9bbf3c8034fd54c0e7412e66edbab6bc74c4996bd616f8d0406e/httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721", size = 12624, upload_time = "2023-12-22T08:01:21.083Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/e1/9b/a181f281f65d776426002f330c31849b86b31fc9d848db62e16f03ff739f/httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f", size = 7819, upload_time = "2023-12-22T08:01:19.89Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "idna"
|
||||||
|
version = "3.10"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/f1/70/7703c29685631f5a7590aa73f1f1d3fa9a380e654b86af429e0934a32f7d/idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9", size = 190490, upload_time = "2024-09-15T18:07:39.745Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442, upload_time = "2024-09-15T18:07:37.964Z" },
|
||||||
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "jiter"
|
||||||
|
version = "0.9.0"
|
||||||
|
source = { registry = "https://pypi.org/simple" }
|
||||||
|
sdist = { url = "https://files.pythonhosted.org/packages/1e/c2/e4562507f52f0af7036da125bb699602ead37a2332af0788f8e0a3417f36/jiter-0.9.0.tar.gz", hash = "sha256:aadba0964deb424daa24492abc3d229c60c4a31bfee205aedbf1acc7639d7893", size = 162604, upload_time = "2025-03-10T21:37:03.278Z" }
|
||||||
|
wheels = [
|
||||||
|
{ url = "https://files.pythonhosted.org/packages/e7/1b/4cd165c362e8f2f520fdb43245e2b414f42a255921248b4f8b9c8d871ff1/jiter-0.9.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:2764891d3f3e8b18dce2cff24949153ee30c9239da7c00f032511091ba688ff7", size = 308197, upload_time = "2025-03-10T21:36:03.828Z" },
|
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Loading…
Reference in New Issue