LexLink

🌐 Read this in other languages: English | 한국어 (Korean)

LexLink is an MCP (Model Context Protocol) server that exposes the Korean National Law Information API (open.law.go.kr) to AI agents and LLM applications. It enables AI systems to search, retrieve, and analyze Korean legal information through standardized MCP tools.

Features

• 26 MCP Tools for comprehensive Korean law information access

  • Search and retrieve Korean laws (effective date & announcement date)

  • Search and retrieve English-translated laws

  • Search and retrieve administrative rules (행정규칙)

  • Query specific articles, paragraphs, and sub-items

  • Law-ordinance linkage (법령-자치법규 연계)

  • Delegated law information (위임법령)

  • Phase 3 - Case Law & Legal Research

    • Court precedents (판례)

    • Constitutional Court decisions (헌재결정례)

    • Legal interpretations (법령해석례)

    • Administrative appeal decisions (행정심판례)

  • Phase 4 - Article Citation Extraction

    • Extract legal citations from any law article (100% accuracy)

  • NEW: Phase 5 - AI-Powered Search

    • Semantic search for natural language queries (aiSearch)

    • Related laws discovery (aiRltLs_search)

• 100% Semantic Validation - All 26 tools confirmed returning real law data

• Session Configuration - Configure once, use across all tool calls

• Error Handling - Actionable error messages with resolution hints

• Korean Text Support - Proper UTF-8 encoding for Korean characters

• Response Formats - HTML or XML (multiple formats supported)

Project Status

🎉 Production Ready - Phase 5 Complete!

Latest Achievement: Phase 5 complete! Added AI-powered semantic search tools (aiSearch, aiRltLs_search) for natural language queries.

Prerequisites

• Python 3.10+

• Smithery API key (optional, for deployment): Get yours at smithery.ai/account/api-keys

• law.go.kr OC identifier: Get key from open.law.go.kr

Quick Start

1. Install Dependencies

2. Configure Your OC Identifier

Choose one of three methods:

Option A: Session Configuration (Recommended)

Option B: Environment Variable

Option C: Pass in Tool Arguments

3. Run the Server

Available Tools

Phase 1: Core Law APIs (6 tools)

1. eflaw_search - Search Laws by Effective Date

Search for laws organized by effective date (시행일 기준).

2. law_search - Search Laws by Announcement Date

Search for laws organized by announcement date (공포일 기준).

3. eflaw_service - Retrieve Law Content (Effective Date)

Get full law text and articles by effective date.

IMPORTANT: For specific article queries (e.g., "제174조"), use the jo parameter. Some laws have 400+ articles and responses can exceed 1MB without jo.

4. law_service - Retrieve Law Content (Announcement Date)

Get full law text and articles by announcement date.

IMPORTANT: For specific article queries (e.g., "제174조"), use the jo parameter. Some laws have 400+ articles and responses can exceed 1MB without jo.

5. eflaw_josub - Query Article/Paragraph (Effective Date)

Best tool for querying specific articles. Returns only the requested article/paragraph.

6. law_josub - Query Article/Paragraph (Announcement Date)

Best tool for querying specific articles. Returns only the requested article/paragraph.

Phase 2: Extended APIs (9 tools)

7. elaw_search - Search English-Translated Laws

Search for Korean laws translated to English.

8. elaw_service - Retrieve English Law Content

Get full English-translated law text.

9. admrul_search - Search Administrative Rules

Search administrative rules (훈령, 예규, 고시, 공고, 지침).

10. admrul_service - Retrieve Administrative Rule Content

Get full administrative rule text with annexes.

11. lnkLs_search - Search Law-Ordinance Linkage

Find laws linked to local ordinances.

12. lnkLsOrdJo_search - Search Ordinance Articles by Law

Find ordinance articles linked to specific law articles.

13. lnkDep_search - Search Law-Ordinance Links by Ministry

Find laws linked to ordinances by government ministry.

14. drlaw_search - Retrieve Law-Ordinance Linkage Statistics

Get linkage statistics table (HTML format).

15. lsDelegated_service - Retrieve Delegated Law Information

Get information about delegated laws, rules, and ordinances.

Phase 3: Case Law & Legal Research (8 tools - NEW!)

16. prec_search - Search Court Precedents

Search Korean court precedents from Supreme Court and lower courts.

17. prec_service - Retrieve Court Precedent Full Text

Get complete court precedent text with case details.

18. detc_search - Search Constitutional Court Decisions

Search Korean Constitutional Court decisions.

19. detc_service - Retrieve Constitutional Court Decision Full Text

Get complete Constitutional Court decision text.

20. expc_search - Search Legal Interpretations

Search legal interpretation precedents issued by government agencies.

21. expc_service - Retrieve Legal Interpretation Full Text

Get complete legal interpretation text.

22. decc_search - Search Administrative Appeal Decisions

Search Korean administrative appeal decisions.

23. decc_service - Retrieve Administrative Appeal Decision Full Text

Get complete administrative appeal decision text.

Phase 4: Article Citation Extraction (1 tool - NEW!)

24. article_citation - Extract Citations from Law Article

Extract all legal citations referenced by a specific law article.

Response:

Key Features:

• 100% accuracy via HTML parsing (not LLM-based)

• Zero API cost (no external LLM calls)

• ~350ms average extraction time

• Distinguishes internal vs external citations

Phase 5: AI-Powered Search (2 tools - NEW!)

25. aiSearch - AI-Powered Semantic Law Search

⭐ PREFERRED TOOL for vague or natural language queries. Use this FIRST when user's intent is unclear or conversational.

Uses intelligent/semantic search to find relevant law articles with full article text.

Best for: Natural language queries like "음주운전 벌금", "이혼 재산분할", "상속 문제"

26. aiRltLs_search - AI-Powered Related Laws Search

⭐ PREFERRED TOOL for discovering related laws from vague topics. Use this when user wants to explore laws around a general subject.

Finds laws semantically related to a given law name or keyword.

Best for: Finding related laws like "민법" → 상법, 의료법, 소송촉진법

Tool Selection Guide

When searching Korean law, select tools based on query clarity:

Configuration

Session Configuration Schema

Configure once in Smithery UI or URL parameters:

Parameter Priority

When resolving the OC identifier:

1. Tool argument (highest priority) - oc parameter in tool call

2. Session config - Set in Smithery UI/URL

3. Environment variable - OC in .env file

Usage Examples

Example 1: Basic Search

Example 2: Search with Date Range

Example 3: Error Handling

Golden MCP Tool Trajectories

These examples demonstrate real-world conversation flows showing how LLMs interact with LexLink tools to answer legal research questions.

Trajectory 1: Basic Law Research

User Query: "What is Article 20 of the Civil Code?"

Tool Calls:

1. law_search(query="민법", display=50, type="XML") → Find Civil Code ID

2. law_service(id="000021", jo="002000", type="XML") → Retrieve Article 20 text

Result: LLM provides formatted explanation of Civil Code Article 20 with full legal text and context.

Trajectory 2: Court Precedent Analysis

User Query: "Find recent Supreme Court precedents about security interests"

Tool Calls:

1. prec_search(query="담보권", curt="대법원", display=50, type="XML") → Search Supreme Court precedents

2. prec_service(id="228541", type="XML") → Retrieve top precedent details

Result: LLM summarizes key precedents with case numbers, dates, and holdings related to security interests.

Trajectory 3: Cross-Phase Legal Research

User Query: "How does the Labor Standards Act handle overtime, and are there relevant court precedents?"

Tool Calls:

1. eflaw_search(query="근로기준법", display=50, type="XML") → Find Labor Standards Act

2. eflaw_service(id="001234", jo="005000", type="XML") → Retrieve Article 50 (overtime provisions)

3. prec_search(query="근로기준법 연장근로", display=30, type="XML") → Search overtime precedents

4. prec_service(id="234567", type="XML") → Retrieve leading precedent

Result: LLM provides comprehensive analysis combining statutory text with judicial interpretation, showing how courts apply the overtime provisions.

Trajectory 4: Constitutional Review

User Query: "Has the Constitutional Court reviewed laws about fines?"

Tool Calls:

1. detc_search(query="벌금", display=50, type="XML") → Search Constitutional Court decisions

2. detc_service(id="58386", type="XML") → Retrieve decision full text

3. law_search(query=<law_name_from_decision>, type="XML") → Find related law for context

Result: LLM explains Constitutional Court holdings on fine-related provisions and their impact on specific laws.

Trajectory 5: Administrative Law Research

User Query: "What administrative rules exist for schools, and are there related legal interpretations?"

Tool Calls:

1. admrul_search(query="학교", display=50, type="XML") → Search school-related administrative rules

2. admrul_service(id="62505", type="XML") → Retrieve rule content

3. expc_search(query="학교", display=30, type="XML") → Search legal interpretations

4. expc_service(id="334617", type="XML") → Retrieve interpretation details

Result: LLM provides overview of administrative framework for schools with official agency interpretations.

Trajectory 6: Comprehensive Legal Analysis

User Query: "I'm researching rental housing disputes. Show me the relevant law, court precedents, and administrative appeal decisions."

Tool Calls:

1. eflaw_search(query="주택임대차보호법", display=50, type="XML") → Find Housing Lease Protection Act

2. eflaw_service(id="002876", type="XML") → Retrieve full law text

3. prec_search(query="주택임대차", display=50, type="XML") → Search housing lease precedents

4. prec_service(id="156789", type="XML") → Retrieve key precedent

5. decc_search(query="주택임대차", display=30, type="XML") → Search administrative appeal decisions

6. decc_service(id="243263", type="XML") → Retrieve appeal decision

Result: LLM provides comprehensive legal research report covering statutory framework, judicial interpretation, and administrative precedents for rental housing disputes.

Trajectory 7: Citation Network Analysis (Phase 4)

User Query: "What laws does Article 3 of the Building Act cite?"

Tool Calls:

1. eflaw_search(query="건축법", display=50, type="XML") → Find Building Act, get MST

2. article_citation(mst="268611", law_name="건축법", article=3) → Extract all citations

Result: LLM provides complete citation analysis showing 12 citations (8 external laws, 4 internal references) including specific article and paragraph references.

Trajectory 8: AI-Powered Natural Language Search (Phase 5)

User Query: "What's the penalty for hit-and-run accidents?"

Tool Calls:

1. aiSearch(query="뺑소니 처벌", search=0, display=20, type="XML") → Semantic search for hit-and-run penalties

Result: LLM receives full article text from relevant laws (특정범죄 가중처벌 등에 관한 법률 제5조의3) with complete provisions about hit-and-run penalties, enabling comprehensive answer without needing to know specific law names.

Trajectory 9: Discovering Related Laws (Phase 5)

User Query: "What laws are related to the Civil Code?"

Tool Calls:

1. aiRltLs_search(query="민법", search=0, type="XML") → Find semantically related laws

Result: LLM discovers related laws like 상법 (Commercial Act), 의료법 (Medical Service Act), 소송촉진법 (Act on Special Cases Concerning Expedition of Litigation), showing connections across legal domains.

Key Patterns

1. AI Tools for Vague Queries: Use aiSearch or aiRltLs_search FIRST when user intent is unclear or conversational

2. Search First, Then Retrieve: Always search to find IDs before calling service tools

3. Use display=50-100 for Law Searches: Ensures exact matches are found due to relevance ranking

4. Combine Phases: Mix Phase 1 (laws), Phase 2 (administrative rules), Phase 3 (precedents), and Phase 5 (AI search) for complete research

5. Type Parameter: Always specify type="XML" for consistent, parseable results

6. Article Numbers: Use 6-digit format (e.g., "002000" for Article 20) when querying specific articles

Development

Project Structure

Running Tests

Adding New Tools

Current Status: 26/26 tools implemented and validated (Phase 1-5 complete)

For implementing additional tools from the 124+ remaining APIs:

1. Follow the pattern established in src/lexlink/server.py

2. Use Context injection for session configuration

3. Use generic parser functions (extract_items_list, update_items_list)

4. Add semantic validation tests

Tool Implementation Pattern:

• Each tool is a decorated function with MCP schema

• Uses ctx: Context = None parameter for session config

• 3-tier parameter resolution: tool arg > session > env

• Generic parser functions work with any XML tag

• Comprehensive error handling with actionable hints

Deployment

Deploy to Smithery

1. Create a GitHub repository:

   git init git add . git commit -m "Initial commit" git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git git push -u origin main

2. Deploy at smithery.ai/new

3. Configure session settings in Smithery UI

Deploy to Kakao PlayMCP (HTTP Server)

LexLink can also be deployed as an HTTP server for platforms like Kakao PlayMCP.

Important: Kakao PlayMCP does not accept port numbers in URLs. You must use Nginx as a reverse proxy to serve on port 80.

Quick Start (Local Testing):

Production Setup:

PlayMCP Registration:

For detailed deployment instructions (AWS EC2, Nginx, systemd, HTTPS), see assets/DEPLOYMENT_GUIDE.md.

PlayMCP Traffic Logging

LexLink includes built-in logging for PlayMCP traffic analysis. Logs are saved in dashboard-compatible JSONL format.

Log Location: logs/playmcp/YYYY-MM-DD.jsonl

Log Schema:

Features:

• Daily log rotation (one file per day)

• Dashboard-compatible format for filtering and analysis

• Captures request/response pairs with timing

• SSE streaming response parsing

Converting Old Raw Logs:

Troubleshooting

"OC parameter is required" error

Solution: Set your OC identifier using one of the three methods above.

Korean characters not displaying correctly

Solution: Ensure your terminal supports UTF-8:

"Timeout" errors

Solution: Increase timeout in session config:

Server won't start after updating dependencies

Solution: Re-sync dependencies:

Contributing

Contributions are welcome! Please:

1. Fork the repository

2. Create a feature branch (git checkout -b feature/amazing-feature)

3. Write tests for new functionality

4. Ensure all tests pass (uv run pytest)

5. Commit changes (git commit -m 'Add amazing feature')

6. Push to branch (git push origin feature/amazing-feature)

7. Open a Pull Request

License

This project is open source. See LICENSE file for details.

Acknowledgments

• law.go.kr - Korean National Law Information API

• MCP - Model Context Protocol by Anthropic

• Smithery - MCP server deployment platform

Support

• Issues: GitHub Issues

• law.go.kr API: Official Documentation

Changelog

v1.3.1 - 2025-12-25

Feature: PlayMCP Traffic Logging

• New Modules:

  • raw_logger.py - Dashboard-compatible MCP traffic logger

  • log_processor.py - Log format converter utility

• Implementation:

  • RawLoggingMiddleware in HTTP server for request/response capture

  • JSONL format with merged request/response pairs

  • Daily log rotation at logs/playmcp/YYYY-MM-DD.jsonl

  • SSE streaming response parsing

• Log Schema:

  • request_id, timestamp, duration_ms

  • method, tool, arguments, result

  • status_code, client_ip, headers

• Impact:

  • Enables traffic analysis for PlayMCP deployments

  • Dashboard-compatible format for monitoring

v1.3.0 - 2025-12-24

Feature: Phase 5 - AI-Powered Search Tools

• New Tools:

  • aiSearch - AI-powered semantic law search (Tool 25)

  • aiRltLs_search - AI-powered related laws search (Tool 26)

• Implementation:

  • Uses law.go.kr's intelligent search system (지능형 법령검색)

  • Semantic search for natural language queries

  • Returns full article text (조문내용) for comprehensive results

  • XML parsing with ranked_data for LLM consumption

• LLM Guidance:

  • Added ⭐ PREFERRED TOOL hints in tool descriptions

  • Added tool-selection-guide MCP prompt for tool selection guidance

  • Tools marked as preferred for vague/unclear queries

• Impact:

  • Tool count: 24 → 26 tools

  • MCP prompts: 5 → 6 prompts

  • Better handling of natural language legal queries

v1.2.9 - 2025-12-09

Fix: Case-insensitive item key matching for API inconsistency

• Issue: law.go.kr API uses inconsistent XML tag casing

  • prec search → <prec> (lowercase)

  • detc search → <Detc> (capitalized)

  • expc search → <Expc> (capitalized)

• Fix: Made extract_items_list, update_items_list, and slim_response case-insensitive

v1.2.8 - 2025-12-09

Fix: Case-sensitive item key extraction for non-law searches

• Issue: extract_items_list() used capitalized keys ('Prec', 'Detc', 'Expc', 'Decc') but XML parser outputs lowercase ('prec', 'detc', etc.)

• Result: ranked_data never set → empty responses for all non-law searches

• Fix: Changed all 8 calls to use lowercase keys

v1.2.7 - 2025-12-09

Refactor: Pattern-based essential field detection

• Issue: Manual field definitions per data type required maintenance for each new API

• Solution: Regex pattern matching for automatic field detection

• Patterns: *일련번호 (IDs), *명한글/*명 (names), *일자 (dates), etc.

• Benefit: Works automatically for any data type without manual definitions

v1.2.6 - 2025-12-09

Fix: Data-type-specific essential fields for slim response

• Issue: slim_response() used law-specific field names for all data types

  • Precedent searches (prec_search) returned empty results

  • Fields like 판례일련번호, 사건명 were filtered out because they didn't match law fields

• Solution:

  • Implemented essential_fields_by_type dictionary with correct fields per data type

  • Each API type (law, prec, detc, expc, decc, admrul, elaw) now has its own essential fields

v1.2.5 - 2025-12-09

Fix: Add 법령ID to essential fields for correct parameter usage

• Issue: LLM was confusing 법령일련번호 (MST) with 법령ID in slimmed responses

  • Example: Calling eflaw_service(id="235555") when 235555 is MST, not 법령ID

  • Correct usage should be eflaw_service(mst=235555) or eflaw_service(id="001624")

• Solution:

  • Added 법령ID back to essential_fields in slim_response()

  • Now LLM can see both fields and use correct parameter

• Essential fields: 법령명한글, 법령일련번호, 법령ID, 현행연혁코드, 시행일자

• Note: If ranking not working, ensure EC2 has latest code with relevance ranking

v1.2.4 - 2025-12-09

Fix: Slim response mode for PlayMCP size limits

• Issue: v1.2.3's truncation approach was insufficient because ranked_data still contained full data (~25KB per 50 results)

• Solution:

  • Replaced truncate_response() with slim_response() function

  • When SLIM_RESPONSE=true: removes raw_content entirely and keeps only essential fields in ranked_data

  • Essential fields kept: 법령명한글, 법령일련번호, 현행연혁코드, 시행일자

  • Fields removed: 법령약칭명, 공포일자, 공포번호, 제개정구분명, 소관부처코드, 소관부처명, 법령구분명, 공동부령정보, 자법타법여부, 법령상세링크

• Configuration:

  • Smithery: No change needed (full response)

  • PlayMCP: Set SLIM_RESPONSE=true in systemd service

• Impact:

  • Response size reduced from ~50KB to ~3-5KB for 50 results

  • PlayMCP works reliably without size errors

v1.2.3 - 2025-12-08

Fix: Response truncation for PlayMCP size limits

• Issue: PlayMCP has response size limits (~50KB), causing "Tool call returned too large content part" errors

• Solution:

  • Added truncate_response() helper function for optional response size limiting

  • Applied truncation to all 11 search tools (eflaw_search, law_search, elaw_search, admrul_search, lnkLs_search, lnkLsOrdJo_search, lnkDep_search, prec_search, detc_search, expc_search, decc_search)

  • Added MAX_RESPONSE_SIZE environment variable (only truncates when set)

• Configuration:

  • Smithery: No change needed (no size limit)

  • PlayMCP: Set MAX_RESPONSE_SIZE=50000 in systemd service

• Impact:

  • Smithery keeps full functionality (unlimited responses)

  • PlayMCP avoids size errors with truncated responses + Korean message

v1.2.2 - 2025-12-06

Feature: HTTP/SSE Server for Kakao PlayMCP

• New Feature:

  • Added HTTP/SSE server support for Kakao PlayMCP deployment

  • New uv run serve command to start HTTP server

  • OCHeaderMiddleware extracts OC from HTTP headers (Key/Token auth)

  • Supports both SSE (/sse) and Streamable HTTP (/mcp) transports

• Breaking Changes:

  • Renamed LAW_OC environment variable to OC (matches official law.go.kr API naming)

• Configuration Changes:

  • Removed base_url from Smithery UI config (kept as internal field only)

  • Updated default timeout from 15s to 60s

  • Timeout range extended to 5-120s

• Documentation:

  • Added Kakao PlayMCP deployment guide (assets/DEPLOYMENT_GUIDE.md)

  • Updated README with PlayMCP deployment section

  • Added http_server.py to project structure

• Impact:

  • LexLink can now be deployed to Kakao PlayMCP and similar HTTP-based platforms

  • Each PlayMCP user provides their own OC via HTTP header (uses their own API quota)

v1.2.1 - 2025-11-30

Fix: Improve LLM guidance for specific article queries

• Issue: LLMs were fetching entire laws (1MB+ for 자본시장법) instead of using jo parameter for specific articles like "제174조"

• Solution:

  • Added IMPORTANT notices in eflaw_service and law_service docstrings about using jo parameter

  • Added BEST TOOL guidance in eflaw_josub and law_josub docstrings

  • Added practical examples: jo="017400" for 제174조, jo="000300" for 제3조

  • Warned about large response sizes (400+ articles, 1MB+ responses)

• Impact:

  • LLMs now correctly use jo parameter for specific article queries

  • LLMs prefer law_josub/eflaw_josub for article queries

  • Faster responses and cleaner output for specific article requests

v1.2.0 - 2025-11-30

Feature: Phase 4 - Article Citation Extraction

• New Tool:

  • article_citation - Extract legal citations from any law article (Tool 24)

• Implementation:

  • HTML parsing approach for 100% accuracy (no LLM hallucination risk)

  • CSS class-based citation type detection (sfon1-4 classes)

  • MST ↔ lsiSeq ID mapping between XML API and HTML pages

  • Zero external API costs (no LLM calls required)

  • ~350ms average extraction time

• Features:

  • Distinguishes internal vs external citations

  • Extracts article, paragraph, and sub-item references

  • Consolidates duplicate citations with citation counts

  • Preserves raw citation text for context

• MCP Prompts Added:

  • extract-law-citations - Extract and explain citations from a law article

  • analyze-citation-network - Analyze legal citation network for a law

• Test Coverage:

  • Unit tests: Citation module 100% coverage

  • Integration tests: End-to-end extraction validated

  • LLM workflow tests: Gemini 2.0 Flash validated

• Known Limitations:

  • Range references (e.g., "제88조 내지 제93조") return first article only

  • External law names require separate search for MST lookup

• Impact:

  • Tool count: 23 → 24 tools

  • MCP prompts: 3 → 5 prompts

  • Enables citation network analysis workflows

v1.1.0 - 2025-11-14

Feature: Phase 3 - Case Law & Legal Research APIs

• Changes:

  • Added 8 new tools for case law and legal research (15 → 23 tools)

  • prec_search, prec_service - Court precedents (판례)

  • detc_search, detc_service - Constitutional Court decisions (헌재결정례)

  • expc_search, expc_service - Legal interpretations (법령해석례)

  • decc_search, decc_service - Administrative appeal decisions (행정심판례)

• Implementation:

  • Added generic parser functions (extract_items_list, update_items_list) that work with any XML tag

  • Added 13 new Phase 3 parameters: prnc_yd, dat_src_nm, ed_yd, reg_yd, expl_yd, dpa_yd, rsl_yd, curt, inq, rpl, itmno, cls

  • All ranking and validation functions compatible with Phase 3 tools

  • Zero breaking changes to existing Phase 1 & 2 tools

• Impact:

  • Tool count increased by 53% (15 → 23 tools)

  • API coverage increased from ~10% to ~15%

  • Legal research categories expanded by 133% (3 → 7 categories)

  • All 23 tools validated and working in production

v1.0.8 - 2025-11-13

Fix: Complete parameter type consistency across all tools

• Issue: v1.0.2 fixed 7 tools but missed 2 additional tools (eflaw_josub, law_josub), creating inconsistency where same parameters had different types across tools

• Root Cause:

  • eflaw_josub and law_josub still had id: Optional[str] and mst: Optional[str] instead of Union[str, int]

  • lnkLsOrdJo_search had jo: Optional[int] instead of Union[str, int]

  • Caused validation errors when LLMs passed integers to these specific tools

• Solution:

  • Fixed eflaw_josub: id and mst now accept Union[str, int]

  • Fixed law_josub: id and mst now accept Union[str, int]

  • Fixed lnkLsOrdJo_search: jo now accepts Union[str, int]

• Verification:

  • All 7 tools with id parameter now consistently Optional[Union[str, int]]

  • All 6 tools with mst parameter now consistently Optional[Union[str, int]]

  • All 5 tools with jo parameter now consistently Optional[Union[str, int]]

• Impact:

  • 100% parameter type consistency achieved

  • No validation errors regardless of which tool LLMs choose

  • Better developer experience - same parameters work identically everywhere

v1.0.7 - 2025-11-10

Fix: Improve search reliability and LLM guidance

• Issue: LLMs often failed to find common laws like "민법" (Civil Code) because:

  1. Ranking fetch limit (50 results) was too small for large result sets (e.g., 77 results for "민법")

  2. LLMs defaulted to small display values (e.g., 5), missing exact matches

  3. jo parameter rejected integers, causing validation errors and retry loops

• Root Cause:

  • v1.0.5 ranking fetched only 50 results; "민법" was beyond position 50 alphabetically

  • Tool descriptions didn't guide LLMs to use larger display values

  • Parameter type strictness caused UX friction

• Solution:

  • Increased ranking fetch limit from 50 to 100 results (API maximum)

  • Updated jo parameter to accept Union[str, int] with auto-conversion

  • Added guidance in tool descriptions: "Recommend 50-100 for law searches (법령 검색) to ensure exact matches are found"

• Changes:

  • All 4 search tools now fetch up to 100 results for ranking

  • All 4 tools with jo parameter (eflaw_service, law_service, eflaw_josub, law_josub) now accept integers

  • All 7 search tool descriptions updated with display recommendations

• Impact:

  • LLMs now find "민법" correctly even with small initial display values

  • No more validation errors when LLMs pass article numbers as integers

  • Better guidance leads to more efficient searches

v1.0.6 - 2025-11-10

Enhancement: Improve MCP server quality score (Smithery.ai optimization)

• Changes:

  • Set OC configuration default value to "test" for easier onboarding

  • Added tool annotations to all 15 tools (readOnlyHint=True, destructiveHint=False, idempotentHint=True)

  • Enhanced parameter descriptions in docstrings for all tools

  • Implemented 3 MCP prompts for common use cases

• Prompts Added:

  • search-korean-law: Search for a Korean law by name and provide a summary

  • get-law-article: Retrieve and explain a specific article from a law

  • search-admin-rules: Search administrative rules by keyword

• Impact: Expected Smithery quality score improvement from 47/100 to ~73/100 (+26 points)

  • Tool annotations: +9pts

  • Parameter descriptions: +12pts

  • MCP prompts: +5pts

v1.0.5 - 2025-11-10

Fix: Improve ranking by fetching more results before ranking

• Issue: v1.0.4 ranking was not working properly because it only ranked the limited results returned by the API (e.g., with display=5, only 5 alphabetically-ordered results were fetched). If "민법" wasn't in those first 5 results, ranking couldn't help.

• Root Cause: Ranking logic was applied AFTER API returned limited results, so relevant matches outside the initial page were never considered.

• Solution:

  • When ranking is enabled and display < 50, automatically fetch up to 50 results from API

  • Apply ranking to the larger result set (50 results)

  • Trim back to original requested display amount after ranking

  • Update numOfRows in response to reflect actual number of results returned

• Implementation:

  • Updated all 4 search tools: eflaw_search, law_search, elaw_search, admrul_search

  • Added original_display tracking and ranking_enabled flag

  • Fetch 50 results when ranking applies, then trim to requested amount

• Examples:

  • User requests display=5 for query "민법"

  • System fetches 50 results (includes "민법" even if it's not in first 5 alphabetically)

  • Ranking places "민법" first

  • System returns top 5 ranked results (now "민법" appears first)

• Impact: Ranking now actually works - exact matches appear first regardless of alphabetical position in API results

v1.0.4 - 2025-11-10

Feature: Add relevance ranking to search results

• Issue: law.go.kr API returns results in alphabetical order, causing irrelevant matches to appear first (e.g., searching "민법" returned "난민법" first instead of exact match "민법")

• Solution:

  • Added intelligent relevance ranking that prioritizes exact matches over alphabetical ordering

  • Ranking applies automatically to XML responses for keyword searches

  • Results are reordered: exact match → starts with query → contains query → other matches

• Implementation:

  • Added ranking.py module with rank_search_results(), should_apply_ranking(), and detect_query_language() functions

  • Added parser.py module for XML parsing and structured data extraction

  • Updated 4 major search tools: eflaw_search, law_search, elaw_search, admrul_search

  • Ranking preserves raw XML while adding ranked_data field for LLM consumption

  • Special handling for elaw_search: Detects query language (Korean vs English) and ranks by matching name field

• Examples:

  • Query "민법" now returns: "민법" (exact) → "민법 시행령" (starts with) → "난민법" (alphabetical)

  • Query "insurance" ranks: "Insurance Act" → "Insurance Business Act" → other matches

• Impact: Significantly improves search relevance, reducing LLM confusion and providing better user experience

v1.0.3 - 2025-11-10

Fix: Clarify article number format in tool descriptions

• Issue: LLMs misinterpreted the 6-digit article number format (jo parameter), generating "000200" for Article 20 (제20조) instead of correct "002000", resulting in wrong article retrieval

• Root Cause: Tool descriptions used ambiguous example "000200" for "Article 2", leading LLMs to incorrectly pattern-match Article 20 → "000200"

• Solution:

  • Added comprehensive article number format documentation with multiple examples

  • Added format_article_number() helper function in validation.py for future use

  • Clarified that XXXXXX format = first 4 digits (article number, zero-padded) + last 2 digits (branch article suffix)

• Changes:

  • Updated 4 tools: eflaw_service, law_service, eflaw_josub, law_josub

  • Updated lnkLsOrdJo_search which uses separate 4+2 digit format

  • Added clear examples: "000200" (Art. 2), "002000" (Art. 20), "001502" (Art. 15-2)

• Impact: LLMs will now correctly format article numbers, preventing queries from returning wrong articles

v1.0.2 - 2025-11-10

Fix: Accept both string and integer for id/mst parameters

• Issue: LLMs extract numeric values from XML responses as integers (e.g., <법령일련번호>188376</법령일련번호> → mst=188376), but tools expected strings, causing Pydantic validation errors

• Solution: Changed parameter types to accept both strings and integers with automatic conversion

• Changes:

  • Updated 7 tool signatures: id: Optional[str] → id: Optional[Union[str, int]]

  • Added automatic string conversion at start of each affected tool

  • Applied to: eflaw_service, law_service, eflaw_josub, law_josub, elaw_service, admrul_service, lsDelegated_service

• Impact: LLMs can now pass numeric IDs as integers without validation errors

v1.0.1 - 2025-11-10

Fix: Remove JSON format option from all tools

• Issue: LLMs were selecting JSON format, but law.go.kr API does not support JSON despite documentation (returns HTML error pages with "미신청된 목록/본문" message)

• Solution: Removed JSON as an option from all 14 tool descriptions

• Changes:

  • Updated type parameter documentation to explicitly state "JSON not supported by API"

  • Added warning in module docstring about JSON format limitation

  • Tool defaults remain XML (working format)

• Impact: Prevents LLMs from requesting JSON format and receiving error pages

v1.0.0 - 2025-11-10

Initial Release

• 15 MCP tools for Korean law information access

• 6 core law APIs (eflaw/law search and retrieval)

• 9 extended APIs (English laws, administrative rules, law-ordinance linkage)

• Session configuration via Context injection

• 100% semantic validation

• Production-ready for Smithery deployment

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