MCP Python Server — API Wrapper
Supports configuration through environment variables for API keys and endpoints, allowing secure storage of authentication credentials
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
MCP Python Server—API Wrapper
This project creates an MCP server in Python that exposes a tool for querying an external API. It is compatible with Claude Desktop or ChatGPT Desktop that support the Model Context Protocol (MCP).
✨ Features
Exposing a tool via MCP
HTTP query to an external API
Direct integration with Claude/Desktop via claude.json
Related MCP server: MCP Starter
🚀 Requirements
Python 3.9+
mcp[cli] (installable via pip or uv)
Claude or ChatGPT Desktop (with MCP support)
📁 Project structure
.
├── servidores/profile.py # Servidor MCP con herramientas para interactuar con mi backend del curriculum.
├── server.py # Servidor MCP con herramienta "consultar_api".
├── .env # Variables opcionales para auth/API.
├── claude.json # Config. MCP para integrarlo directamente.
└── README.md # Este documento.⚙️ Installation
With pip
pip install "mcp[cli]"With UV (recommended)
uv init mcp-api-server
cd mcp-api-server
uv add "mcp[cli]"Installation of the MCP
mcp install mi_script.pyInstallation with .env
mcp install mi_script.py -f .envInstallation of dependencies
pip install -r requirements.txtEnvironment variables
Create a .env file in the project root to define optional environment variables:
# .env
API_KEY=mi_api_key
API_URL=https://miapi.com/consulta👷 Quick Start (Quickstart)
Create the server server.py
from mcp.server.fastmcp import FastMCP
import httpx
mcp = FastMCP("API Wrapper")
@mcp.tool(description="Consulta una API externa")
async def consultar_api(param: str) -> str:
"""Consulta una API externa con un parámetro y devuelve la respuesta."""
async with httpx.AsyncClient() as client:
r = await client.get(f"https://miapi.com/consulta?param={param}")
return r.textRun locally in dev mode
mcp dev server.pyRun in production mode
mcp run server.pyOr with uv:
uv run --with mcp[cli] mcp run server.py🚀 Integration with Claude/Desktop
Locate claude.json in the Claude/Desktop configuration folder:
On Windows: %APPDATA%\Claude\claude.json
On Linux/macOS: ~/.claude/claude.json
Example:
{
"mcpServers": {
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/codigo/backend-curso-inkor/proyectos_memes"
]
},
"Demo": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"C:\\codigo\\backend-curso-inkor\\MCP\\server.py"
]
}
}
}🤖 Use within Claude/Desktop
You can ask the model:
Use the consult_api tool with the "ping" parameter
And the model will use your MCP server to make a real-time HTTP call.
🎁 Bonus: Tools Extension
@mcp.tool()
async def traducir(texto: str, lang: str) -> str:
return f"Traducido: {texto} → {lang}"🔍 Resources
Official MCP documentation: https://docs.mcp.run/
Python SDK repository: https://github.com/modelcontextprotocol/mcp
✅ Made with love and httpx 🚀
This server cannot be deployed
Maintenance
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