Interactions with large language models (LLMs) in model context protocol (MCP) environments often feel unnatural due to generic tool descriptions that lack context, leading to inefficient tool routing. This issue arises because tools like retrieval or text-to-SQL are labeled with vague descriptions, making it difficult for LLMs to choose the correct tool without explicit instructions from users, which interrupts conversational flow. To address this, Context-Aware Tools dynamically generate descriptions based on the specific content or schema they access, providing LLMs with the necessary context to make accurate decisions independently. This approach eliminates the need for prompt engineering or rigid rules, allowing for more natural and seamless interactions. Ragie has implemented this concept through Dynamic FastMCP, an open-source library that enables dynamic tool descriptions by sampling and summarizing knowledge base content, updating them in real-time to reflect relevant topics. This method enhances multi-tenant SaaS environments by ensuring per-tenant, context-specific tool descriptions, improving tool routing without altering the existing MCP protocol or requiring changes to client-side integrations.