AI Agents with Model Context Protocol
About this course
This Specialization teaches learners to build production-ready AI agents using TypeScript and the Model Context Protocol (MCP), focusing on the agentic patterns that make agents reliable, efficient, and autonomous. Learners master designing tool servers that connect agents to real-world systems, implementing the universal agent loop, and applying critical patterns like Response-as-Instruction (treating LLM outputs as executable directives), Failing Forward (using errors as learning signals rather than stop conditions), and Intelligence Budget (optimizing token spend across reasoning steps). Graduates can ship AI agents that discover context dynamically, recover from errors automatically, and operate effectively in production environments.
90/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
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What you'll learn
- design tool servers for AI agents
- implement the universal agent loop
- apply Response-as-Instruction
- utilize Failing Forward strategies
- manage Intelligence Budget for token optimization
Course objectives
- build production-ready AI agents
- connect agents to real-world systems
- foster agentic patterns for reliability and autonomy
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