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FastAPI with MCP: Build Intelligent Python APIs with Model-Text Protocols

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En stock

Peso con empaque:
0.72 kg

Devolución:
Sí

Condición
Nuevo

Producto de:
Amazon

Sobre este producto

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)
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
FastAPI · MCP Protocol · Uvicorn & Gunicorn · Docker · Poetry · OpenTelemetry · Prometheus · Jaeger · APScheduler · Pydantic · JWT · Streamlit · React · LLM Toolchains

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U$S 72,48

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U$S 28,99

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FastAPI with MCP: Build Intelligent Python APIs with Model-Text Protocols

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