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completed the flask-mcp-compare servers
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‎flask-mcp-compare/README.md‎

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# Flask MCP Server Comparison
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## Setting up the Environment
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Execute the below commands on your terminal /
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command prompt
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### Pre Requisites:
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- Python
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- Pip
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- Git
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- Anthropic API key
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Update the anthropic API key in the .env file
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### Steps to execute:
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1. Clone the repo
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git clone
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https://github.com/insightbuilder/codeai_fusion.git
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2. Change into flask-mcp-compare folder:
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cd flask-mcp-compare
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3. Create virtual environment
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python -m venv .venv
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Ensure the .venv folder is created. Add that
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folder to your .gitignore
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4. Activate virtual environment
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source .venv/bin/activate in linux
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.venv\Scripts\activate in windows
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5. Install requirements
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pip install -r requirements.txt
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#### Running the Flask App
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python flaskapp.py
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#### Running the MCP Server
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python mcpclient.py mcpserver.py

‎flask-mcp-compare/flask-mcp-compare.md‎

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# Flask MCP Server Comparison
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## Setting up the Environment
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Execute the below commands on your terminal /
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command prompt
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### Pre Requisites:
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- Python
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- Pip
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- Git
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- Anthropic API key
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Update the anthropic API key in the .env file
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### Steps to execute:
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1. Clone the repo
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git clone
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https://github.com/insightbuilder/codeai_fusion.git
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2. Change into flask-mcp-compare folder:
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cd flask-mcp-compare
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3. Create virtual environment
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python -m venv .venv
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Ensure the .venv folder is created. Add that
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folder to your .gitignore
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4. Activate virtual environment
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source .venv/bin/activate in linux
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.venv\Scripts\activate in windows
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5. Install requirements
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pip install -r requirements.txt
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#### Running the Flask App
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python flaskapp.py
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#### Running the MCP Server
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python mcpclient.py mcpserver.py

‎flask-mcp-compare/flaskapp.py‎

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from flask import Flask, render_template, request
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app = Flask(__name__)
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@app.route("/", methods=["GET", "POST"])
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def index():
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bmi = None
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category = None
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if request.method == "POST":
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weight = float(request.form.get("weight", 0))
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height = float(request.form.get("height", 0)) / 100 # convert cm to meters
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if height > 0:
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bmi = round(weight / (height**2), 2)
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if bmi < 18.5:
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category = "Underweight"
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elif bmi < 25:
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category = "Normal weight"
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elif bmi < 30:
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category = "Overweight"
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else:
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category = "Obese"
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return render_template("index.html", bmi=bmi, category=category)
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if __name__ == "__main__":
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app.run(debug=True)

‎flask-mcp-compare/mcpclient.py‎

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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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# pyright: reportMissingImports=false
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# pyright: reportOptionalSubscript=false
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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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# uncomment this when running in your local environment
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# ensure you have updated the .env file with the Anthropic API Key
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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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# methods will go here
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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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Args:
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server_script_path: Path to the server script (.py or .js)
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"""
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is_python = server_script_path.endswith(".py")
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is_js = server_script_path.endswith(".js")
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if not (is_python or is_js):
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raise ValueError("Server script must be a .py or .js file")
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command = "python" if is_python else "node"
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server_params = StdioServerParameters(
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command=command, args=[server_script_path], env=None
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)
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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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self.stdio, self.write = stdio_transport
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self.session = await self.exit_stack.enter_async_context(
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ClientSession(self.stdio, self.write)
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)
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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 = [{"role": "user", "content": query}]
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response = await self.session.list_tools()
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available_tools = [
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{
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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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}
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for tool in response.tools
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]
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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-haiku-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({"role": "assistant", "content": content.text})
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messages.append({"role": "user", "content": result.content})
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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-haiku-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 mcpclient.py mcpserver.py")
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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())

‎flask-mcp-compare/mcpserver.py‎

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from mcp.server.fastmcp import FastMCP
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mcp = FastMCP("Echo")
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@mcp.tool()
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def bmi_calculator(weight: float, height: float) -> str:
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"""Calculates the BMI using the given weight and height, and returns the value"""
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if height > 0 and weight > 0:
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bmi = round(weight / (height**2), 2)
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return f"Your BMI: {bmi}"
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return "Height and weight have to be more than 0"
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@mcp.tool()
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def custom_eqn(a: float, b: float, d: float) -> float:
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"""Performs a custom equation with the given parameters and returns the result"""
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x = 25
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c = a + b * b
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return a * (x ^ 3) - b * (x ^ 2) + c * x - d
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if __name__ == "__main__":
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print("Starting MCP server...")
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mcp.run()

‎flask-mcp-compare/requirements.txt‎

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mcp[cli]
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mcp
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python-dotenv
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flask
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anthropic

‎flask-mcp-compare/static/style.css‎

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body {
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font-family: Arial, sans-serif;
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background: #f3f3f3;
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margin: 0;
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padding: 0;
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}
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.container {
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max-width: 600px;
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margin: 40px auto;
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padding: 30px;
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background: #fff;
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border-radius: 12px;
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box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
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}
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.calculator h2 {
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color: #4CAF50;
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}
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form {
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display: flex;
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flex-direction: column;
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}
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input, button {
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padding: 10px;
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margin: 8px 0;
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border-radius: 6px;
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border: 1px solid #ccc;
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}
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button {
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background: #4CAF50;
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color: white;
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border: none;
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cursor: pointer;
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}
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.result {
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margin-top: 20px;
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background: #e7f3e7;
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padding: 10px;
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border-left: 4px solid #4CAF50;
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}
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