{"id":10600,"date":"2026-02-04T07:21:23","date_gmt":"2026-02-04T06:21:23","guid":{"rendered":"https:\/\/kaleidoscope.at\/blog\/bessere-ki-ergebnisse-durch-terminology-augmented-generation-und-mcp\/"},"modified":"2026-02-12T16:00:09","modified_gmt":"2026-02-12T15:00:09","slug":"better-ai-results-through-tag-and-mcp","status":"publish","type":"blog","link":"https:\/\/kaleidoscope.at\/en\/blog\/better-ai-results-through-tag-and-mcp\/","title":{"rendered":"Optimizing GenAI: Better AI Results Through Terminology-Augmented Generation (TAG) and MCP"},"content":{"rendered":"\n

Despite significant investment in generative AI (GenAI), many companies are still struggling to use it effectively. Inaccurate output, a lack of context, and inconsistent wording are just some of the challenges regularly faced. In this article you'll discover how your structured terminology database can be used to massively increase the precision and efficiency of your AI output through terminology-augmented generation (TAG) and the Quickterm MCP server.<\/strong>\u00a0<\/p><\/div>\n\n\n\n

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Key Takeaways<\/h2><\/div>\n\n\n\n
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<\/path><\/svg><\/span>Challenges of Generative AI<\/strong>: Many companies continue to struggle with inaccurate outputs, lack of context, and inconsistencies in communication, hindering the effective use of Generative AI (GenAI).<\/span><\/div>\n\n\n\n
<\/path><\/svg><\/span>Solution through TAG and MCP<\/strong>: Terminology-augmented generation (TAG) and the Quickterm MCP server allow for terminology to be used as a structured knowledge base, significantly enhancing the accuracy and efficiency of GenAI.<\/span><\/div>\n\n\n\n
<\/path><\/svg><\/span>Effectiveness of TAG<\/strong>: The application of TAG has resulted in significant improvements in terminology adherence and precision of translations, minimizing issues such as hallucinations in AI applications.<\/span><\/div>\n\n\n\n
<\/path><\/svg><\/span>Model Context Protocol (MCP)<\/strong>: MCP provides a standardized interface for accessing external data sources and facilitates easy and efficient integration with LLMs (Large Language Models), reducing the implementation effort for corporate IT.<\/span><\/div>\n\n\n\n
<\/path><\/svg><\/span>Future of terminology in companies<\/strong>: The integration of terminology into AI projects is critical to their success; TAG via MCP ensures that existing terminological resources in companies are optimally utilized, leading to a higher return on investment.<\/span><\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\t\t\t\t
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  1. Key Takeaways<\/a>
  2. GenAI: from hype to market maturity<\/a>
  3. Why AI projects fail:\u00a0current efficiency problems<\/a>
  4. But why is this?<\/a>
  5. The solution: terminology, TAG & MCP<\/a>