Posts
All the articles I've posted.
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MCP Study #3 — What Resources / Prompts Actually Are + Integration with LangGraph (`MultiServerMCPClient` · `ainvoke`)
Beyond Tools covered in #1 / #2, this post covers the other two components of MCP: Resources (data for the LLM to read, background context, read-only) and Prompts (predefined templates). I check a new server with Inspector + Claude Desktop → integrate the MCP server into LangGraph using langchain-mcp-adapters. Covers why `ainvoke` is needed since MCP communication is asynchronous, the secret behind how MultiServerMCPClient loads servers as-is (= MCP standard compliance), and the difference in domain response quality when injecting Resources as a system prompt.
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MCP Study #2 — Connecting My MCP Server to Claude Desktop · Tool Calls + Approval UX
Actually connecting the energy-management MCP server I built yesterday to Claude Desktop. From finding claude_desktop_config.json (Settings → Developer → Edit Config) → registering the server → restarting → checking the connectors menu → asking 'show me the factory line list' and watching Claude call the tool with the 'Always Allow/Deny' approval UX. Question raised: how do you use RAG and MCP together? (Answer: wrap RAG in an MCP server)
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FEMS Project #3 — Streamlit Comparison Dashboard + 3-Backend Question Evaluation (Claude 9 / exaone 7 / gpt 7)
Put a Streamlit dashboard on top of FEMS RAG and threw the same question at 3 backends (exaone3.5:7.8b / claude-opus-4-8 / gpt-4o) simultaneously to compare. Q1 (air compressor anomaly in May) — exaone and gpt said 'no data', while Claude inferred 'weekend-hours anomaly' from summary stats alone without raw data + disclosed its limitations. Q2 (savings measures from a manager's perspective) — Claude 9/10 (incomplete due to token truncation), exaone 7/10 (broken index), gpt 7/10 (concise but hallucinated 'capacitor'). Results of 5-axis scoring.
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MCP Study #1 — Getting Started with Model Context Protocol · First Call with stdio Server + Inspector
Starting to study MCP (Model Context Protocol) today. It's a standard protocol created by Anthropic that standardizes how LLMs access external systems. Comparing it with Tool Use → building my first MCP server (say_hello / add_numbers) with the Python SDK → verifying the stdio connection with MCP Inspector → building a fake energy management server that connects with FEMS. Connection failure due to venv python.exe path issue + fix.