🚀 Build an MCP Server from Scratch with FastAPI & WebSockets + Client AI agent with text-to-sql 😎✨

In this epic tutorial, we’ll guide you through every step of creating a 🔥 Model Context Protocol (MCP) server using FastAPI, WebSockets, Pydantic, and async/await in Python. Whether you’re building intelligent agents, real-time apps, or just geeking out on custom protocols, this video has everything you need! 🤖💬

Resources & Code:

What You’ll Learn:

🎯 MCP Fundamentals: Discover why a custom Model Context Protocol is the secret sauce for AI-driven clients, and how it standardizes communication between your Python agent and server.

🗂️ Project Structure Deep Dive: Explore the MCPFromScratch repo layout—separating server 📦 vs. client 🤖 logic—and learn why modular tools, prompts, and resources keep your code clean and extensible.

⚡ FastAPI Setup & Lifespan Management:

Use an asynccontextmanager to manage your application’s lifespan: automatically connect to SQLite and initialize your in-memory key-store on startup, and cleanly tear down on shutdown.

Dual-Mode Operation: Your server will handle both HTTP REST requests (for health checks, tool/prompt listing & HTTP-based calls) and a real-time WebSocket /mcp endpoint—giving you the flexibility to choose the communication style that fits your use case.

🛠️ Registering Server Capabilities:

Tools: Define callable functions (e.g., math ops, text-to-SQL converters).

Prompts: Create LLM templates (summaries, translations).

Resources: Expose URI-style data endpoints (user profiles, configs).

Invocation Endpoints: Execute these capabilities via RESTful HTTP or over the WebSocket channel.

🛡️ Security & Quotas:

API-Key Authentication: All HTTP endpoints and every WebSocket connection validate X-API-Key headers to ensure only authorized clients connect.

Request Quota Management: Track and enforce per-key usage limits with your in-memory key store to prevent abuse and ensure fair access.

🌐 Real-Time WebSockets: Maintain a persistent /mcp session for bidirectional messaging—manage concurrent read/write loops, stream progress updates, and deliver low-latency responses.

🚀 Async/Await Mastery: Keep your server non-blocking—juggle database queries, external API calls, and WebSocket messages like a pro.

🧩 End-to-End Client Agent: We’ll build an AI assistant that:

Converts natural-language queries into SQL using your server’s specialized tool.

Executes that SQL on the MCP server.

Transforms the raw results into a friendly, conversational answer.
All coded line-by-line so you can follow along!

🛡️ Extending & Scaling: Learn how to add custom tools (image processing, analytics), design new resource URIs, version your API, and integrate with front-end applications.

Why You’ll ❤️ This:
By the end, you’ll have a fully functional MCP server running in dual-mode (REST & WebSocket), complete with tools, prompts, resources, lifecycle management, API-key security, and quota enforcement—and a Python client agent that magically turns plain-English questions into SQL queries and back again. You’ll gain hands-on experience with cutting-edge Python frameworks and design patterns powering tomorrow’s intelligent services. 🌟

If this deep dive pumped you up, LIKE, COMMENT, and SUBSCRIBE for more Python, FastAPI, and AI architecture goodness! Hit the 🔔 to never miss an update. 🙌🎉

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