sample-okf-llm-wiki vs stashbase
sample-okf-llm-wiki: Data Wiki converts AWS data sources like Glue Data Catalog and Redshift into portable, AI-authored knowledge bundles, making complex data semantics accessible to AI agents. It uses LLMs to generate markdown documentation for datasets, including tables, joins, and metrics, and serves these via the Model Context Protocol (MCP).; stashbase: StashBase enables AI agents to search and utilize content from your local files, including PDFs, DOCX, images, audio, and video. It creates a searchable index from your folders, allowing agents to find relevant context by meaning rather than just keywords.
TL;DR
Enabling AI agents to understand complex AWS data semantics.
- You want a desktop app that indexes folders of PDFs, DOCX, images, audio and video and shares them with Claude, Codex and other MCP clients.
- Your files must stay the source of truth: the index can be rebuilt, and removing a folder never deletes files.
- You want exact text search with no key, and semantic search only if you opt in.
- Your documents cannot leave the machine and you need semantic search: it sends content to OpenAI or OpenRouter.
- You are on Linux and need official support: Linux builds are community-supported.
- You only need one file converted now and then: an MCP converter is lighter.
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