MCP for dummies: Feed more context to LLM
summary
Claims that Model Context Protocol standardizes passing external context to models and reduces per-tool custom work and function-calling glue. Implementation uses JSON-RPC 2.0 over either stdio subprocesses or streamable HTTP (SSE-like) transport. Demo builds an MCP server around a quadrant vector DB, connects it to an agent using Gemini 2.5 Pro and a Streamlit UI, saves a generated poem to the vector DB and successfully retrieves it. Observability via OPIC and concrete security warnings about prompt/tools injection and supply‑chain risk are shown.
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chapters (14)
- 0:00MCP and context engineering
- 3:35Problems with large language models
- 4:57Model Context Protocol
- 7:28MCP client-server interaction
- 9:56MCP transport mechanisms
- 11:21Building MCP servers
- 14:57Existing MCP servers
- 17:04MCP security concerns
- 21:19Demo: MCP with agents
- 23:04Setting up MCP server
- 25:11System prompts for agents
- 27:18UI with Streamlit
- 29:03Demo: MCP in action
- 30:26Resources and tips
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