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：https://github.com/Marktechpost/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：https://www.linkedin.com/in/arnav-rai-475033243/ (CS student at Rochester Institute of Technology) during his internship at Marktechpost, supervised by Jean-marc Mommessin：https://www.linkedin.com/in/contactjmm/ and Asif Razzaq：https://www.linkedin.com/in/asifrazzaq/. Token Saver fundamentally changes how Claude interacts with local documents. By implementing a Local Hybrid RAG ：https://github.com/Marktechpost/Token-Saver (system directly on your machine, it allows you to ask questions about massive PDFs without ever uploading the actual file to the model.
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 core issue: the entire document still crosses the boundary to the provider’s servers. Furthermore, if you only need two relevant paragraphs from a 1,000-page textbook, forcing the LLM to search the entire 1,000 pages itself is both inefficient and prone to hallucination.
Marktechpost’s Token Saver ：https://github.com/Marktechpost/Token-Saver acts as a local MCP server : a lightweight background program on your machine that Claude can call as a tool. The PDF never leaves your hard drive.
When you ask a question, Token Saver utilizes Local Hybrid RAG to find the answer. Hybrid RAG is the gold standard for document retrieval because it combines two powerful search methods:
By blending these two approaches locally, the server searches the file and hands Claude only the highly relevant passages. Claude then synthesizes the answer, citing the exact page numbers and providing a running tally of the tokens you just saved.
Token Saver：https://github.com/Marktechpost/Token-Saver runs entirely inside a single, long-running local process. Before any text reaches Claude, the local Hybrid RAG pipeline executes eight rapid steps:
(Note: The embedding model is optional but recommended. If it fails to load, the system gracefully falls back to keyword-only matching).
Because the Hybrid RAG pipeline caps the returned text slice, the token savings grow exponentially with the size of the document. Here is how Token Saver performed in benchmarking (measured via tiktoken, assuming one question per document):
Disclaimer: Token counts use cl100k_base as a stand-in, and baselines assume the whole document is charged on every search.
For professionals working repeatedly with court opinions, technical standards, financial reports, or dense textbooks, Token Saver eliminates the repetitive token tax.
Marktechpost’s Token Saver works across all three Claude 3.5 tiers, but testing revealed distinct behaviors:
Unlike many open-source AI tools that require complex Python environments and JSON configurations, Token Saver is packaged as a single .mcpb bundle.
The extension will not run until a folder is chosen, because that single choice serves three purposes at once.
That folder is worth a moment’s thought. It sets the boundary of what can be read, it is what lets you ask for a file by name instead of typing a path, and it is the list the server shows Claude when a conversation starts. A small folder holding only what you intend to ask about works considerably better than pointing it at all of Documents.
Check out the GitHub Repo：https://github.com/Marktechpost/Token-Saver.
References: MCP Bundle format：https://github.com/anthropics/mcpb | all-MiniLM-L6-v2：https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 | pdfkb-mcp：https://github.com/juanqui/pdfkb-mcp | wesleygriffin/pdfrag：https://github.com/wesleygriffin/pdfrag | Corpora: Dobbs v. Jackson Women’s Health Organization ; Berkshire Hathaway 2023 Annual Report
Arnav is currently a student at Rochester Institute of Technology pursuing a Bachelor’s degree in Computer Science and a minor in Economics with hands-on backend development experience, and is a contributor at Marktechpost, where he writes about AI/ML research.
Jean-marc is a successful AI business executive .He leads and accelerates growth for AI powered solutions and started a computer vision company in 2006. He is a recognized speaker at AI conferences and has an MBA from Stanford.
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
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