Update dependencies and add comprehensive examples
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stabgan
187
examples/python_example.py
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187
examples/python_example.py
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#!/usr/bin/env python3
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"""
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OpenRouter MCP Server - Python Example
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This script demonstrates how to use the OpenRouter MCP Server from Python,
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for various tasks such as text chat and image analysis.
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"""
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import os
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import sys
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import json
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import asyncio
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import subprocess
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from typing import Optional, Dict, Any, List
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from contextlib import AsyncExitStack
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from dotenv import load_dotenv
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# Try to import MCP client libraries, show a helpful error if not available
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try:
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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except ImportError:
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print("Error: MCP client libraries not found. Please install them with:")
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print("pip install python-mcp")
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sys.exit(1)
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# Try to import OpenAI, show a helpful error if not available
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try:
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from openai import OpenAI
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except ImportError:
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print("Error: OpenAI client not found. Please install it with:")
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print("pip install openai")
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sys.exit(1)
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# Load environment variables from .env file
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load_dotenv()
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# Get API key from environment, or show error
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API_KEY = os.getenv("OPENROUTER_API_KEY")
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if not API_KEY:
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print("Error: OPENROUTER_API_KEY environment variable is missing")
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print("Please create a .env file with OPENROUTER_API_KEY=your_key")
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sys.exit(1)
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# Default model to use
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MODEL = "anthropic/claude-3-5-sonnet"
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# Configuration for the MCP server
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SERVER_CONFIG = {
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"command": "npx",
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"args": ["-y", "@stabgan/openrouter-mcp-multimodal"],
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"env": {"OPENROUTER_API_KEY": API_KEY}
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}
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def convert_tool_format(tool):
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"""Convert MCP tool definition to OpenAI tool format"""
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converted_tool = {
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"type": "function",
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"function": {
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"name": tool.name,
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"description": tool.description,
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"parameters": {
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"type": "object",
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"properties": tool.inputSchema["properties"],
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"required": tool.inputSchema["required"]
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}
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}
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}
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return converted_tool
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class MCPClient:
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"""MCP Client for interacting with the OpenRouter MCP server"""
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def __init__(self):
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self.session: Optional[ClientSession] = None
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self.exit_stack = AsyncExitStack()
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self.openai = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=API_KEY
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)
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self.messages = []
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async def connect_to_server(self, server_config):
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"""Connect to the MCP server"""
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server_params = StdioServerParameters(**server_config)
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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 from the MCP server
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response = await self.session.list_tools()
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print("\nConnected to server with tools:", [tool.name for tool in response.tools])
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return response.tools
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async def process_query(self, query: str) -> str:
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"""Process a text query using the MCP server"""
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self.messages.append({
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"role": "user",
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"content": query
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})
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# Get available tools from the MCP server
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response = await self.session.list_tools()
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available_tools = [convert_tool_format(tool) for tool in response.tools]
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# Make the initial OpenRouter API call with tool definitions
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response = self.openai.chat.completions.create(
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model=MODEL,
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tools=available_tools,
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messages=self.messages
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)
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self.messages.append(response.choices[0].message.model_dump())
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final_text = []
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content = response.choices[0].message
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# Process tool calls if any
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if content.tool_calls is not None:
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tool_name = content.tool_calls[0].function.name
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tool_args = content.tool_calls[0].function.arguments
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tool_args = json.loads(tool_args) if tool_args else {}
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# Execute tool call
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try:
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result = await self.session.call_tool(tool_name, tool_args)
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final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")
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except Exception as e:
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print(f"Error calling tool {tool_name}: {e}")
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result = None
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# Add tool result to messages
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self.messages.append({
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"role": "tool",
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"tool_call_id": content.tool_calls[0].id,
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"name": tool_name,
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"content": result.content if result else "Error executing tool call"
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})
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# Make a follow-up API call with the tool results
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response = self.openai.chat.completions.create(
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model=MODEL,
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max_tokens=1000,
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messages=self.messages,
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)
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final_text.append(response.choices[0].message.content)
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else:
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final_text.append(content.content)
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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() in ['quit', 'exit']:
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break
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result = await self.process_query(query)
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print("Result:")
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print(result)
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except Exception as e:
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print(f"Error: {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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"""Main entry point for the example script"""
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client = MCPClient()
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try:
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await client.connect_to_server(SERVER_CONFIG)
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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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asyncio.run(main())
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