FastAPI AI Agent Skills

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

FastAPI best practices and patterns for building modern Python web APIs

You are an expert in Python, FastAPI, and scalable API development.

Python FastAPI .cursorrules

You are an expert in Python, FastAPI, and scalable API development.

Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".

You are an expert in Python, FastAPI, and scalable API development.

Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and

Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.

Master Python 3.12+ with modern features, async programming,

GenAI Agent Framework, the Pydantic way Documentation: ai.pydantic.dev FastAPI revolutionized web development by offering an innovative and ergonomic design, built on the foundation of Pydantic Validation and modern Python features like type hints. Yet despite virtually every Python agent framework and LLM library using Pydantic Validation, when we began to use LLMs in Pydantic Logfire, we couldn'

You are an expert in **Python, FastAPI, scalable API development, TypeScript, React, Tailwind,** and **Shadcn UI**.

Here are some best practices and rules you must follow:

Your AI Assistant in Memory Forensics Volatility MCP seamlessly integrates Volatility 3's powerful memory analysis with FastAPI and the Model Context Protocol (MCP). Experience memory forensics without barriers as plugins like pslist and netscan become accessible through clean REST APIs, connecting memory artifacts directly to AI assistants and web applications Volatility 3 Integration: Leverages

A lightweight MCP (Model Context Protocol) server for ODBC built with FastAPI, pyodbc, and SQLAlchemy. This server is compatible with Virtuoso DBMS and other DBMS backends that implement a SQLAlchemy provider. - Get Schemas: Fetch and list all schema names from the connected database. - Get Tables: Retrieve table information for specific schemas or all schemas. - Describe Table: Generate a detaile

A Model Context Protocol (MCP) server for weather data, built with FastAPI and the MCP framework. This server provides various weather-related tools that can be used by AI assistants to retrieve current weather conditions, forecasts, air quality data, and more. - Current weather conditions - Weather forecasts (1-14 days) - Historical weather data - Weather alerts - Air quality information - Astron

Create FastAPI routers with CRUD operations, authentication dependencies, and proper response models. Use when building REST API endpoints, creating new routes, implementing CRUD operations, or adding authenticated endpoints in FastAPI applications.

Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.

An experimental and educational Ping-Pong server demonstrating MCP (Model Context Protocol) calls via FastAPI. - ✅ FastAPI/FastMCP backend for remote MCP calls through API endpoints or SSE - 🔄 MCP integration for command handling - 🔐 Thread-safe session management To install the dependencies, run: Start the FastAPI server with: The server will start at http://localhost:8080. Open mcp-api-client.