stashbase
★ 1.1k
vs
wet
★ 19
stashbase vs wet
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.; wet: WET is an open-source MCP server designed to empower AI agents with advanced web capabilities. It provides web search, content extraction, and library documentation indexing, offering comprehensive data retrieval for agent-driven tasks.
01
TL;DR
stashbaseRAG / Knowledge Base · ★ 1.1k
When to choose:
- 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.
When to skip:
- 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.
wetRAG / Knowledge Base · ★ 19
AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making.
02
Side-by-Side Comparison
Field
stashbasewetCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 1.1k
★ 19
License
Apache-2.0
Apache-2.0
Install Command
brew install --cask liliu-z/stashbase/stashbase
pip install wet
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
Local Files, RAG, AI Agents
AI Agents, Web Search, Content Extraction
03
Features
stashbase01Extracts searchable text from various formats including PDFs, DOCX, images (OCR), audio, and video (transcription).
02Semantic search capabilities to find relevant context by meaning, supported by an AI Index.
03Connects and shares searchable context across Claude, Codex, and other MCP clients and built-in agents.
04Maintains local files as the source of truth, with indexes and derived data stored separately.
wet01Web Search: Embedded SearXNG metasearch (Google, Bing, DuckDuckGo, Brave) with query expansion, TTL cache, standardized citation format, and 200-token snippet cap. Optional cloud search backends as a fallback chain.
02Academic Research: Search across major academic databases including Google Scholar, Semantic Scholar, arXiv, PubMed, CrossRef, and BASE.
03Library Docs: Automatically discover and index library documentation using FTS5 hybrid search, HyDE-enhanced retrieval, and support for version-specific queries.
04Content Extraction: Utilizes a 5-strategy escalation chain for robust URL content extraction, producing smart chunks with structured output (text, markdown, JSON-LD, code blocks, metadata), supports batch processing, deep crawling, local file conversion, and includes anti-bot strategies.
05Zero Config Fallbacks: Offers out-of-the-box functionality with built-in local reference embedding and reranking via fastretrieval, requiring no API keys, while also supporting optional cloud providers for enhanced quality.
04
Use Cases
stashbase↳Providing AI agents with searchable access to research papers and contracts stored locally.
↳Enabling chatbots to answer questions based on internal documentation, scanned documents, and recordings.
↳Developers wanting to query project design documents and architecture notes using a built-in AI agent.
↳Organizing and searching personal knowledge bases that primarily consist of diverse local file types.
wet↳AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making.
↳Automated Research & Knowledge Gathering: Automate academic and library documentation research, efficiently gathering and providing structured information to AI agents for analysis and synthesis.
↳Content Analysis & Summarization: Facilitate advanced content extraction from URLs and local files, preparing data for in-depth analysis, summarization, or integration into Retrieval-Augmented Generation (RAG) systems.
↳Developer Documentation Lookup: Grant AI agents version-aware access to comprehensive library and project documentation, aiding in coding assistance, debugging, and issue resolution.
05
Best For
stashbaseTrending
wet—
FAQ
FAQ
What is the difference between stashbase and wet?
Both stashbase and wet are in the RAG / Knowledge Base category. stashbase has 1.1k stars, while wet has 19 stars.
Which is better, stashbase or wet?
The best choice depends on your use case. Choose stashbase if Providing AI agents with searchable access to research papers and contracts stored locally., and wet if AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making..
Is stashbase free or open source?
Yes, stashbase is open source on GitHub (Apache-2.0).
Is wet free or open source?
Yes, wet is open source on GitHub (Apache-2.0).
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