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Case Study

KiMCP

MCP server that exposes Korean APIs (Naver, Kakao, TMAP) as tools for LLM applications and agent workflows.

Python 3.10+ MCP Python SDK uv HTTPX Korean Open APIs
KiMCP screenshot

Project Overview

KiMCP (Korea-integrated Model Context Protocol) is an MCP server that helps LLM applications use Korean web and map APIs through a unified tool interface. It focuses on practical integrations needed by Korean-language assistant products.

Key Features

  • Naver Search Tools: Blog, news, cafe, knowledge iN, image, local, and shopping search
  • Daum Search Tools: Blog and cafe integrations
  • Navigation Integrations: Kakao map search plus driving and transit routing through Kakao/TMAP
  • Tool-level Fallback Behavior: API-specific tools can be enabled/disabled by available keys
  • Claude Desktop Integration: Supports direct install and local inspection workflows

Technical Challenges & Solutions

Challenge 1: API heterogeneity

Unified multiple provider APIs behind MCP-compatible tools with consistent input/output patterns.

Challenge 2: Operational flexibility

Designed key-dependent tool activation so partial setups still provide useful capabilities.

Challenge 3: Developer onboarding

Kept setup friction low with uv workflows and direct mcp install / mcp dev commands.

What I Learned

  • Building MCP-native tool servers for real assistant use cases
  • Designing interfaces across API ecosystems with different conventions
  • Balancing broad coverage and maintainable Python service architecture
  • Improving local DX for agent tooling experimentation

Impact

KiMCP expands what Korean-focused LLM assistants can do by connecting local data and navigation ecosystems to MCP-compatible clients.