Real-World Agentic AI With MCP Standards : Building an RFP Analyzer That Writes Its Own Proposals

Our intention is to make new technologies & emerging tools installation easy for students, beginners & experienced professionals.

In this in-depth project walkthrough, we build a powerful, real-world Agentic AI system from scratch designed to solve a major pain point for IT service and consulting companies: the time-consuming process of analyzing a Request for Proposal (RFP) and writing a high-level technical proposal.

Join me as we transform a process that takes teams of experts weeks into an automated task that completes in just minutes. We'll go beyond simple scripts and construct a true AI agent with its own set of specialized tools, a sophisticated reasoning loop, and an interactive web UI. You'll see the entire end-to-end flow, from uploading a raw RFP document to downloading a professionally formatted, multi-page design proposal.

This video is perfect for developers, AI engineers, and solution architects who want to move beyond basic chatbot examples and build practical, valuable agentic systems.

🚀 What You'll Learn in This Video:

1. Real-World Use Case: A detailed breakdown of the RFP-to-Proposal lifecycle and how AI can revolutionize it.
2. Agentic AI Architecture: How to structure an agent with a "think" loop and specialized tool servers using the Model Context Protocol (MCP).
3. Custom Tool Creation: We'll build two essential servers from scratch:
4. Document Ingestor: To read and extract text from PDFs (PyMuPDF) and Word documents (python-docx).
5. Report Generator: To create beautiful, professional PDFs from Markdown without needing LaTeX, using WeasyPrint and markdown2.
6. Advanced Prompt Engineering: The secret sauce! We'll explore how to write detailed, multi-step prompts that guide the LLM (Google Gemini) to perform a complex sequence of tasks reliably.
7. Interactive UI & Conversational AI: See a live demo of the Gradio application, and learn about the future roadmap to evolve this agent into a conversational "AI Consultant" with stateful deep-dive analysis.


🔧 Tech Stack & Libraries Covered:
AI Model: Google Gemini 1.5 Flash with library google.generativeai
Agent Framework: Custom-built using Python & the Model Context Protocol (MCP-FastMCP)
UI: Gradio
PDF/Document Handling: PyMuPDF, python-docx, WeasyPrint, markdown2
Core Libraries: asyncio, aiofiles, python-dotenv

Thank you for watching! If you're excited about building practical AI solutions, please like, subscribe, and hit the notification bell so you don't miss the next video where we'll implement the "deep dive" feature!

#AgenticAI #GenerativeAI #Python #GoogleGemini #ArtificialIntelligence #llm #ai #mcp