Semantic Tool Discovery for Large Language Models: A Vector-Based Approach to MCP Tool Selection
#semantic tool discovery #large language models #vector-based approach #MCP tool selection #AI efficiency #semantic similarity #tool discovery
📌 Key Takeaways
- A vector-based approach is proposed for semantic tool discovery in LLMs.
- The method enhances MCP tool selection by understanding semantic similarity.
- It aims to improve efficiency in connecting LLMs with appropriate external tools.
- The approach addresses challenges in discovering relevant tools from large sets.
📖 Full Retelling
arXiv:2603.20313v1 Announce Type: cross
Abstract: Large Language Models (LLMs) with tool-calling capabilities have demonstrated remarkable potential in executing complex tasks through external tool integration. The Model Context Protocol (MCP) has emerged as a standardized framework for connecting LLMs to diverse toolsets, with individual MCP servers potentially exposing dozens to hundreds of tools. However, current implementations face a critical scalability challenge: providing all available
🏷️ Themes
AI Tools, Semantic Search
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Original Source
arXiv:2603.20313v1 Announce Type: cross
Abstract: Large Language Models (LLMs) with tool-calling capabilities have demonstrated remarkable potential in executing complex tasks through external tool integration. The Model Context Protocol (MCP) has emerged as a standardized framework for connecting LLMs to diverse toolsets, with individual MCP servers potentially exposing dozens to hundreds of tools. However, current implementations face a critical scalability challenge: providing all available
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