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Designing Multi-Agent Systems with NLWeb and MCP: Orchestrate Interoperable Networks of Specialized AI Agents to Discover, Query, and Process Web Data
Paperback
Series: The AI Systems Architect, Book 1
Publisher: Independently Published
Published: May 23 2026
Pages: 190
Weight: 0.75
Height: 0.40 Width: 7.00 Depth: 10.00
Language: English
Build agentic web systems that move beyond fragile scraping, scattered APIs, and isolated chatbots.
Modern AI teams need more than prompts. They need agents that can discover tools, query structured web data, coordinate with other agents, route tasks safely, and process live information without breaking every time a website changes. How do you design that kind of system without creating a brittle mess of scripts, tokens, and unreliable automation?
Designing Multi-Agent Systems with NLWeb and MCP gives developers, architects, and AI engineers a practical blueprint for building interoperable networks of specialized AI agents using Microsoft NLWeb, Model Context Protocol, structured retrieval, tool routing, and production-ready orchestration patterns. The manuscript positions NLWeb and MCP as core building blocks for machine-to-machine web interaction, with coverage of MCP server architecture, NLWeb ask workflows, vector pipelines, specialized retrieval agents, AgentFinder, DataFinder, multi-agent handoffs, cost engineering, and enterprise guardrails.
Inside, you'll learn how to:
- Set up reliable Python and Node.js environments for agent systems
- Build MCP servers, tools, resources, prompts, and structured payloads
- Connect NLWeb-style query flows to semantic search and live data sources
- Design specialized agents for search, comparison, routing, and task handoff
- Improve cost, latency, token efficiency, validation, and production safety
- Apply security gates, human approvals, and deployment-ready guardrails
This book is for software engineers, AI engineers, system architects, backend developers, and technical leaders who want to build practical agentic web infrastructure instead of one-off automation scripts.
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