MCP Python Server — API Wrapper
MCP Python Server – API Wrapper
Dieses Projekt erstellt einen MCP-Server in Python, der ein Tool zum Abfragen einer externen API bereitstellt. Kompatibel mit Claude Desktop oder ChatGPT Desktop, die das Model Context Protocol (MCP) unterstützen.
✨ Funktionen
Verfügbarmachen eines Tools über MCP
HTTP-Abfrage an eine externe API
Direkte Integration mit Claude/Desktop über claude.json
Related MCP server: MCP Starter
🚀 Voraussetzungen
Python 3.9+
mcp[cli] (installierbar über pip oder uv)
Claude oder ChatGPT Desktop (mit MCP-Unterstützung)
📁 Projektstruktur
.
├── 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
Mit Pip
pip install "mcp[cli]"Mit UV (empfohlen)
uv init mcp-api-server
cd mcp-api-server
uv add "mcp[cli]"Installation des MCP
mcp install mi_script.pyInstallation mit .env
mcp install mi_script.py -f .envInstallation von Abhängigkeiten
pip install -r requirements.txtUmgebungsvariablen
Erstellen Sie eine .env Datei im Projektstamm, um optionale Umgebungsvariablen zu definieren:
# .env
API_KEY=mi_api_key
API_URL=https://miapi.com/consulta👷 Schnellstart (Schnellstart)
Erstellen Sie den 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.textLokal im Entwicklermodus ausführen
mcp dev server.pyIm Produktionsmodus ausführen
mcp run server.pyOder mit UV:
uv run --with mcp[cli] mcp run server.py🚀 Integration mit Claude/Desktop
Suchen Sie claude.json im Konfigurationsordner Claude/Desktop:
Unter Windows: %APPDATA%\Claude\claude.json
Unter Linux/macOS: ~/.claude/claude.json
Beispiel:
{
"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"
]
}
}
}🤖 Verwendung innerhalb von Claude/Desktop
Sie können das Modell fragen:
Verwenden Sie das Tool consult_api mit dem Parameter „ping“
Und das Modell verwendet Ihren MCP-Server, um einen HTTP-Aufruf in Echtzeit zu tätigen.
🎁 Bonus: Tools-Erweiterung
@mcp.tool()
async def traducir(texto: str, lang: str) -> str:
return f"Traducido: {texto} → {lang}"🔍 Ressourcen
Offizielle MCP-Dokumentation: https://docs.mcp.run/
Python SDK-Repository: https://github.com/modelcontextprotocol/mcp
✅ Mit Liebe gemacht und httpx 🚀
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