stashbase vs mxLore
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.; mxLore: mxLore is a self-hosted server designed to provide persistent memory for AI coding assistants by storing architectural decisions, specifications, and lessons learned. It integrates with various AI clients like Claude Code and Cursor, enabling multi-project knowledge management and AI-driven insights.
TL;DR
- 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.
Centralized storage and retrieval of architectural decisions and project specifications.
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