Fastapi Mcp In Python
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FastAPI with MCP
Author: Drake Duncan
language: en
Publisher: Independently Published
Release Date: 2025-06-11
Unlock the power of intelligent API development with FastAPI and Model-Text Protocols (MCP). This comprehensive and practical guide teaches backend developers, API engineers, and AI system architects how to integrate FastAPI, Python's blazing-fast web framework, with MCP (Model-Text Protocol) to create scalable, agentic, and intelligent applications. Whether you're building structured LLM workflows, chaining agent tasks, or deploying microservice-style AI pipelines, this book provides a hands-on roadmap using the most up-to-date tools and practices. Inside You'll Learn: How to build clean, production-ready FastAPI endpoints integrated with LLM-based agents Understanding and implementing the MCP message structure for model-to-agent communication Managing tools, prompts, and agent logic with reusable patterns and scalable design Running background tasks, cron jobs, and real-time agent calls Observability, logging, and tracing with tools like OpenTelemetry and Prometheus Dockerizing and deploying your FastAPI + MCP stack to Render, Fly.io, or a VPS Full project: Build and deploy a multi-agent system with FastAPI, MCP, and a front-end interface (Streamlit or React) Whether you're building agent-driven AI backends, experimenting with LangChain-style chaining, or just getting started with structured LLM protocols in Python, this book delivers expert-level guidance without the fluff. Who This Book Is For: Backend developers and Python programmers working with APIs Engineers deploying AI agents or LLM workflows using FastAPI Professionals seeking real-world, containerized deployment strategies AI system architects adopting structured agent messaging and tool chaining Technologies Covered: FastAPI - MCP Protocol - Uvicorn & Gunicorn - Docker - Poetry - OpenTelemetry - Prometheus - Jaeger - APScheduler - Pydantic - JWT - Streamlit - React - LLM Toolchains Drake Duncan is a software engineer, backend architect, and technical author with deep expertise in Python-based systems, distributed architecture, and modern API design. With years of hands-on experience building production systems and AI-driven services, Drake is known for writing clear, structured, and practical programming books that help developers level up with confidence.
FastAPI & MCP in Python
Author: TODD. CHANDLER
language: en
Publisher: Independently Published
Release Date: 2025-05-22
FastAPI & MCP in Python: Build High-Performance AI Agent Services Are you ready to build next-generation AI agent services-fast, reliable, and production-ready? If you want to design robust agent pipelines, integrate powerful tools, and scale your AI solutions with confidence, this book delivers everything you need. This comprehensive guide brings together FastAPI-the leading Python web framework for modern APIs-and the Model Context Protocol (MCP), an emerging standard for agent communication. You'll move step-by-step from foundational concepts to advanced, real-world implementations. No abstract theory-just proven, practical strategies, clear explanations, and fully working code. What sets this book apart? Essential Building Blocks: Learn how to structure your FastAPI projects, manage dependencies, and implement security best practices. Hands-On Agent Pipelines: Follow detailed walkthroughs for creating MCP-compliant services, from tool definition and request-reply handlers to streaming, error handling, and tool orchestration. Real-World Features: Discover how to add authentication, logging, monitoring with Prometheus, and tracing with OpenTelemetry. Explore advanced concurrency patterns, serverless deployment with AWS Lambda, and resilient error recovery. Testing and CI/CD: Master automated unit, integration, and contract testing. Streamline delivery with ready-to-use CI/CD pipelines for quality and speed. Actionable Guides: Put knowledge into practice with hands-on projects: weather alert tools, research assistant pipelines, interactive dashboards, and more. Are you looking for a guide that balances clarity, depth, and hands-on practicality? This book is packed with examples, concise tips, and solutions to common challenges faced by modern Python developers building agentic systems. Take your AI services from idea to production-order your copy of "FastAPI & MCP in Python: Build High-Performance AI Agent Services" today and start building with confidence.
Building MCP Clients in Python
Author: Timothy Kertzmann
language: en
Publisher: Independently Published
Release Date: 2025-06-16
Building MCP Clients in Python: A FastAPI Developer's Guide Are you ready to master a modern standard that is transforming how AI models, APIs, and automation tools connect seamlessly? This book offers a hands-on, practical guide to building robust MCP (Model Context Protocol) clients in Python using FastAPI-one of the fastest, most developer-friendly frameworks available. Building MCP Clients in Python explores the fundamentals of MCP, a protocol designed to standardize communication between intelligent systems and external tools. You'll learn how to build scalable, secure, and maintainable clients that leverage real-time streaming, structured tool discovery, typed schemas, and seamless integration with large language models and external APIs. With a focus on practical implementation, this guide walks you through every step-from setting up your environment and crafting your first client, to advanced features like authentication, error handling, testing, deployment, and extending MCP capabilities. What sets this book apart is its comprehensive coverage structured into clearly focused chapters, including: Foundations of MCP and FastAPI: Understand MCP's architecture and why FastAPI is ideal for modern API development. Deep Dive into MCP Protocol: Learn about JSON-RPC, Server-Sent Events, schema generation, and tool discovery. Building and Connecting MCP Clients: Step-by-step guidance to create clients, connect securely, invoke operations, and handle streaming data. Advanced Features and Security: Implement authentication, error handling, caching, and best security practices for reliable clients. Testing, Deployment, and Full-Stack Solutions: Strategies for writing tests, deploying with Docker and Kubernetes, and building full-stack MCP-powered systems. Ecosystem and Community: Stay current with MCP tools, libraries, and standards. Whether you are a Python developer aiming to integrate cutting-edge AI workflows, build automated business tools, or explore scalable API design, this book equips you with practical knowledge and runnable examples to accelerate your projects confidently. Ready to build the future of AI-powered integrations? Start your journey with Building MCP Clients in Python and turn complex protocols into reliable, production-ready applications.