Meet Token Saver: An Open-Source MCP Extension Using Local Hybrid RAG to Cut Claude PDF Token Costs 90-99%
AI developers, researchers, and professionals frequently hit a frustrating wall when analyzing large documents with LLMs: the hidden, compounding cost of context windows. Pasting a 200-page PDF into a chat isn’t a one-time charge. Because the conversation history is re-sent to the model on every single turn, that massive document is paid for again with every follow-up question. Marktechpost AI team just released Token Saver, an open-source Model Context Protocol (MCP) extension for Cla
Token Saver is an open-source extension that allows Claude to analyze PDF documents stored locally on a user's machine without uploading the files to external servers. The tool uses a hybrid retrieval system combining keyword matching and semantic search to extract only the relevant passages from a document, then sends those passages to Claude rather than the entire file. This approach reduces token consumption by 92 to 99 percent because users are charged only for the small relevant sections rather than the full document on every question. The extension matters because repeatedly asking questions about large PDFs normally requires re-sending the entire document with each follow-up query, creating significant costs, while Token Saver keeps documents private and limits what gets processed by the language model.
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