Meet Token Saver: An Open-Source MCP Extension Using Local Hybrid RAG to Cut Claude PDF Token Costs 90-99%

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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 Claude Desktop (MIT licensed, currently at v1.0). It was developed at Marktechpost AI Media Inc by Arnav Rai (CS student at Rochester Institute of Technology) during his internship at Marktechpost, supervised by Jean-marc Mommessin and Asif Razzaq. Token Saver fundamentally changes how Claude interacts with local documents. By implementing a Local Hybrid RAG (system directly on your machine, it allows you to ask questions about massive PDFs without ever uploading the actual file to the model.

Token consumption is slashed by 92% to 99%, privacy is guaranteed, and setup requires exactly zero Python environments or terminal configurations.

How it looks!

The Hidden Token Drain of Large PDFs

Most users assume that when they drop a PDF into Claude, it simply extracts the text. In reality, Claude’s default behavior converts each page into an image to preserve charts and layouts, while separately extracting text. Before a single image token is even counted, the text alone can run 1,500 to 3,000 tokens per page.

While Prompt Caching and Claude Projects help soften this blow, they don’t solve the …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen: Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://www.marktechpost.com/2026/07/30/token-saver-an-open-source-mcp-extension-using-local-hybrid-rag/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.