ArXiv MCP Server: Add enhanced LLM-friendly tool descriptions and restored blazickjp functionality

[jasonleinart]

---

name: Add a new MCP server
about: Requests for adding a new MCP server to the Docker Catalog
title: ""
labels: submission
assignees: ""

Summary

This PR builds upon the previous merge (#170) by adding
the complete restored functionality from the original
blazickjp repository, addressing the core issue
identified in feedback where LLMs would skip using the
ArXiv tools.

What's New in This Update

🔧 Restored Core Functionality

• VALID_CATEGORIES validation system - Complete
  arXiv category validation
• Enhanced helper functions -
  _validate_categories(), _optimize_query(),
  _build_date_filter()
• Advanced sorting options - Sort by relevance or
  date
• Comprehensive error handling - Improved logging
  and error messages

🧠 LLM-Friendly Tool Descriptions

The enhanced search tool now includes detailed
documentation that LLMs can understand:

description: |
  QUERY CONSTRUCTION GUIDELINES:
  - Use QUOTED PHRASES for exact matches: "multi-agent 
systems", "neural networks" 
  - Field-specific searches: ti:"exact title phrase", 
au:"author name"
  - Advanced patterns: au:"Hinton" AND "deep learning" 
with categories: ["cs.LG"]
  
  EXAMPLES OF EFFECTIVE QUERIES:
  - ti:"reinforcement learning" with categories: 
["cs.LG", "cs.AI"]
  - "multi-agent" ANDNOT "survey" with categories: 
["cs.MA"]

Problem Solved

Addresses the specific feedback issue:
"LLMs never try to use the tools in this server, because
 they cannot understand what they do or how to use them.
 When I ask an AI to 'search ArXiv for recent AI 
advancements' it skips directly to searching 
DuckDuckGo."

Technical Changes

- Source repository: Points to enhanced
jasonleinart/arxiv-mcp-server with restored blazickjp
functionality
- Enhanced descriptions: 2,400+ character tool
descriptions with concrete examples
- Category validation: Complete arXiv category prefix
validation
- Query optimization: Intelligent query processing while
 preserving user intent

Testing & Verification

- ✅ Production tested: Actual paper downloads and
processing verified
- ✅ Docker container: Full functionality tested in
production environment
- ✅ LLM integration: Tool descriptions verified to
guide LLM usage effectively
- ✅ Local catalog: Successfully generated and validated

Impact

This update ensures LLMs will actively choose and
effectively use the ArXiv tools instead of falling back
to web search, providing researchers with proper
academic paper discovery and analysis capabilities.