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Learn how to build an MCP client that bridges your application logic with server capabilities. This tutorial covers the two-layer client architecture, implementing core methods, and testing the complete flow.
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Resources in MCP allow your server to expose data that can be directly included in prompts, rather than requiring tool calls to access information. This creates a more efficient way to provide context to AI models like Claude.- Published on
Learn how to process PDF documents with Claude for intelligent analysis beyond simple text extraction. Covers implementation, what Claude can extract from PDFs, common use cases like contract analysis and data extraction, and production best practices.- Published on
Stop using one-size-fits-all prompts. Learn how routing workflows categorize user requests and send them to specialized pipelines for better, more consistent results. Includes real-world examples and implementation best practices.- Published on
Stop letting users reinvent the wheel. Learn how to create battle-tested prompts in MCP servers that deliver consistent, high-quality results every time. Complete guide covering server-side implementation, client integration, and best practices.