Find your files with natural language and ask questions.
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"iflow-mcp-shredengineer-archive-agent","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
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 --- # Archive Agent *An intelligent file indexer with powerful AI search (RAG engine), automatic OCR, and a seamless MCP interface.*   [](https://github.com/Andrew-Jang/RAGHub?tab=readme-ov-file#rag-projects) [](https://mcphub.com/mcp-servers/shredEngineer/Archive-Agent) [](https://mcp.so/server/Archive-Agent/shredEngineer) [](https://mseep.ai/app/499d8d83-02c8-4c9b-9e4f-8e8391395482) [](https://deepwiki.com/shredEngineer/Archive-Agent) **Archive Agent** brings RAG to your command line and connects to your tools via MCP — it's *not* a chatbot. --- ## Find what you need with natural language - **Unlock your documents with semantic AI search & query** - Files are split using [semantic chunking with context headers](#how-smart-chunking-works) and committed to a local database. - [RAG engine](#how-chunks-are-retrieved)**¹** uses [reranking and expanding](#how-chunks-are-reranked-and-expanded) of retrieved chunks **¹** *[Retrieval Augmented Generation](https://en.wikipedia.org/wiki/Retrieval-augmented_generation) is the method of matching pre-made snippets of information to a query.* --- ## Natively index your documents on-device - **Includes local AI file system indexer** - Natively ingests [PDFs, images, Markdown, plaintext, and more…](#which-files-are-processed) - [Selects and tracks files using patterns](#how-files-are-selected-for-tracking) like `~/Documents/*.pdf` - Transcribes images using [automatic OCR](#ocr-str…
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