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MCP vs API: Simplifying AI Agent Integration with External Data
IBM’s video pits two integration patterns—generic REST APIs and the purpose‑built Model Context Protocol (MCP)—against the real‑world demands of AI agents
Does MCP Kill Vector Search?
3 Design Questions the LlamaIndex Article Answers:
🔍 1. When can you safely punt structured queries to federated MCP, and when do you still need a unified index?
⚡️ 2. What performance and UX trade-offs arise between federated calls vs. centralized RAG?
🧩 3. How do you architect a hybrid pipeline that leverages the strengths of both?
Which MCP Server is for me?
3 Selection Criteria the Medium Article Presents:
🔌 1. Where will the server run?
☕ 2. Which language runtime lines up with your team and compliance rules?
🛡️ 3. How will you handle state, security, and future protocol changes?
Implementing Identity-Aware MCP Servers
3 Questions the Medium Article Answers:
🔑 1. Which OAuth 2.0 roles and grant flows actually matter for an MCP stack?
🔒 2. How do tokens flow through an identity-aware MCP call path?
🛠️ 3. What implementation hurdles show up in real life?
Model Context Protocol — Intuitively and Exhaustively Explained
5 Questions the Medium Article Answers:
❓ 1. What pain-point is MCP trying to solve?
⚙️ 2. How does MCP actually work?
📣 3. Why keep hearing “MCP is the LSP of AI”?
🧰 4. What do I need to build a minimal MCP demo?
🔮 5. Where might MCP go next?