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AST Grep and Transform

Automating code updates at scale can be tricky, especially when it comes to maintaining accuracy. Abstract Syntax Trees (AST) offer a powerful solution by allowing you to directly manipulate code structures without worrying about formatting inconsistencies. With tools like ast-grep and LLMs, you can locate, transform, and update code efficiently. This approach is ideal for tasks such as generating or updating function documentation in TypeScript projects. Curious how this works? Explore how AST-driven strategies can streamline your workflow.

MCP Resources

The Model Context Protocol (MCP) introduces a powerful way for scripts to provide context to large language models (LLMs) by exposing data through MCP resources. These resources enable servers to share structured content that clients can access and utilize efficiently. By integrating publishResource into your workflows, you can streamline how your applications interact with MCP clients, enhancing context discovery and resolution. Dive deeper into how MCP tools and resources can elevate your systems today.

Blog Images

Automatically generating blog post cover images may sound mundane, but the script behind the process showcases some interesting automation techniques. By transforming the markdown content into an image prompt, generating visuals and alt text, and seamlessly updating metadata, this multi-step workflow demonstrates how small-scale automation can scale efficiently. The result? Abstract, content-driven images that hint at optimization potential. Thought-provoking for content creators considering automation workflows.

Scripts as MCP tools!

The Model Context Protocol (MCP) is reshaping how we approach integration with AI-driven tools. Platforms like GitHub Copilot Chat and Copilot Studio are leading adoption efforts, and GenAIScript is now enabling you to expose scripts as MCP tools, streamlining workflows with smarter decision-making by LLMs. Ready to elevate your development process? Explore the details in the documentation.

Azure AI Search

Discover how GenAIScript simplifies interaction with Azure AI Search for building vector-based search systems. With built-in support for chunking, vectorization, and indexing, you can efficiently implement Retrieval Augmented Generation (RAG) workflows, leveraging embeddings for similarity searches across your data. Learn how to streamline file indexing and query execution using straightforward functions and enhance your AI toolset.