The aleostudio MCP Server is a lightweight Python server that provides AI agents with utility tools through the Model Context Protocol (MCP).
Available Tools:
calculate - Perform basic mathematical operations (add, subtract, multiply, divide, power)
get_datetime - Retrieve current date/time with configurable timezone offsets (UTC -12 to +14) and multiple output formats (ISO, human-readable, Unix timestamp, components)
process_text - Analyze and manipulate text with operations including word/character counting, case conversion (uppercase, lowercase, title case, reverse), email/URL extraction, and statistics summaries
fetch_url - Execute HTTP GET/HEAD requests to retrieve content, headers, and status codes from URLs
convert_data - Convert data between formats including JSON, Base64, and Hexadecimal
Deployment Options:
STDIO mode for local integration (e.g., Claude Desktop)
SSE mode for remote agent access via HTTP
Extensible architecture for creating custom tools following the provided template
Compatible with Python 3.11+ with VSCode debugging support and MCP Inspector testing
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@aleostudio MCP Servercalculate 125 multiplied by 8"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Simple MCP server with tools for AI agents
A fast and lightweight MCP server with different tools for AI agents. It supports STDIO (Claude Desktop) and SSE (remote agents).
Index
Prerequisites
Python >= 3.11
uv and pip installed
Configuration
Init virtualenv and install dependencies with:
Create your .env file by copying:
Then, customize it if needed.
Run server in STDIO mode
First of all, to test the server, install and run a MCP Inspector with:
At the end, a UI will open in your browser. Connect to the server by clicking Connect on the left menu.
Then, from the top bar, click on Tools and List tools. At this point you can choose you preferred tools and play with it.
If you want to test it without the inspector, simply launch with:
Run server in SSE mode
If you want to use the server through SSE from remote agents, launch it with:
As the STDIO mode, you can test it with MCP Inspector (remote) with:
If you want to simulate a tool call from a remote agent, create a simple STDIO client in python (e.g. stdio_test.py) with this code:
Then run with:
You will see a the available tools list and the result of calculate.
Configure Claude Desktop
If you want to use tools on Claude Desktop, create the file claude_desktop_config.json with this content:
Move this file in:
macOS:
~/Library/Application Support/ClaudeWindows:
%APPDATA%\Claude
Available tools
Tool | Descrizione |
| Math operations (add, subtract, multiply, divide, power) |
| Date/hour with timezone and configurable format |
| Text handler (word count, extract email/URL, stats) |
| HTTP GET/HEAD requests |
| JSON, Base64, Hex conversions |
Create new tool
To create new tool you need to:
Create a new file (e.g.
app/tools/my_new_tool.py)Write your logic keeping this structure:
from app.mcp import mcp @mcp.tool() def my_new_tool(your_param: str) -> dict[str, Any]: """ Clear and exaustive tool description. Args: your_param: clear and exaustive param description Returns: Clear and exaustive result description """ # YOUR LOGIC HERE if some_error: return {"success": False, "error": "Clear error description"} return { "success": True, "your_resp": "...", "other_resp": "...", }Edit
app/tools/__init__.pyfile and add your tool:from app.tools import my_new_tool __all__ = [ "my_new_tool", ]Restart your server
In the same way, if you want to delete an existing tool, simply delete it from __init__.py and delete the related .py file.
Debug in VSCode
To debug your Python microservice you need to:
Install VSCode
Ensure you have Python extension installed
Ensure you have selected the right interpreter with virtualenv on VSCode
Click on Run and Debug menu and create a launch.json file
From dropdown, select Python debugger and FastAPI
Change the
.vscode/launch.jsoncreated in the project root with this (customizing host and port if changed):
Put some breakpoint in the code, then press the green play button
Call the API to debug
Made with ♥️ by Alessandro Orrù