How do I use aleostudio MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@aleostudio MCP Server calculate 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).

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Prerequisites

Python >= 3.11
uv and pip installed

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Configuration

Init virtualenv and install dependencies with:

uv venv source .venv/bin/activate uv sync

Create your .env file by copying:

cp env.dist .env

Then, customize it if needed.

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Run server in STDIO mode

First of all, to test the server, install and run a MCP inspector with:

npx @modelcontextprotocol/inspector uv run python server.py

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:

uv run python server.py

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Run server in SSE mode

If you want to use the server through SSE from remote agents, launch it with:

uv run python server.py --sse --port 8000

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:

import asyncio from mcp import ClientSession, StdioServerParameters from mcp.client.stdio import stdio_client async def test(): server_params = StdioServerParameters(command="uv", args=["run", "python", "server.py"], cwd="./") async with stdio_client(server_params) as (read, write): async with ClientSession(read, write) as session: await session.initialize() # Tools list tools = await session.list_tools() print("Tools:", [t.name for t in tools.tools]) # Call calculate result = await session.call_tool("calculate", { "operation": "multiply", "a": 6, "b": 7 }) print("Result:", result.content) asyncio.run(test())

Then run with:

python3 stdio_test.py

You will see a the available tools list and the result of calculate.

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Configure Claude Desktop

If you want to use tools on Claude Desktop, create the file claude_desktop_config.json with this content:

{ "mcpServers": { "mcp-server-tools": { "command": "uv", "args": ["run", "--directory", "/path/to/mcp-server", "python", "server.py"] } } }

Move this file in:

macOS: ~/Library/Application Support/Claude
Windows: %APPDATA%\Claude

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Available tools

Tool	Descrizione
`calculate`	Math operations (add, subtract, multiply, divide, power)
`get_datetime`	Date/hour with timezone and configurable format
`process_text`	Text handler (word count, extract email/URL, stats)
`fetch_url`	HTTP GET/HEAD requests
`convert_data`	JSON, Base64, Hex conversions

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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.json created in the project root with this (customizing host and port if changed):

{ "version": "0.2.0", "configurations": [ { "name": "MCP Server (SSE)", "type": "debugpy", "request": "launch", "program": "server.py", "args": [ "--sse" ], "envFile": "${workspaceFolder}/.env", "console": "integratedTerminal", "cwd": "${workspaceFolder}", "justMyCode": true }, { "name": "MCP Server (STDIO)", "type": "debugpy", "request": "launch", "program": "server.py", "envFile": "${workspaceFolder}/.env", "console": "integratedTerminal", "cwd": "${workspaceFolder}", "justMyCode": true } ] }