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Design AI work that outlives one HTTP request with background execution, polling, webhooks, persistence, cancellation, deduplication, and recovery.
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Understand MCP 2026-07-28 interactive workflows: stateless requests, Multi Round-Trip Requests, elicitation, explicit state handles, and the Tasks extension.
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Understand MCP authorization with OAuth 2.1, PKCE, resource metadata, issuer validation, resource indicators, credential isolation, and client registration.
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A practical MCP security checklist for clients and users: server identity, OAuth, tool permissions, argument review, prompt injection, data exfiltration, retries, and revocation.
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Understand how MCP tools differ from model function calling, how they fit together, what each layer controls, and why the distinction matters for security.
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Compare OpenRouter with direct AI provider APIs across model choice, billing, privacy, native features, routing, reliability, debugging, and everyday BYOK use.
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Learn how client-managed history, provider-side conversation state, response IDs, local persistence, privacy, portability, and recovery fit together in AI chat apps.
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A practical explanation of OpenAI-compatible APIs, what compatibility actually means, what can still differ, how to test an endpoint, and when to use one.
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Learn what the Model Context Protocol is, how MCP tools fit into an AI chat workflow, and why permissions and server trust matter.
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