rag-rat
★ 24
vs
stashbase
★ 1.1k
rag-rat vs stashbase
rag-rat: rag-rat is a local repository intelligence index and MCP server that provides coding agents with deep, source-anchored insights into a codebase. It builds a comprehensive code graph, integrates Git/GitHub history, and stores durable repo memories to offer provenance-backed answers about code rationale and impact.; 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.
01
TL;DR
rag-ratRAG / Knowledge Base · ★ 24
Code Impact Analysis: Understand the blast radius of a code change by querying callers, callees, tests, recent commits, and associated repo memories before editing.
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.
02
Side-by-Side Comparison
Field
rag-ratstashbaseCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 24
★ 1.1k
License
MIT
Apache-2.0
Install Command
npm install -g @rag-rat/bin && rag-rat init --yes && npx @rag-rat/skills
brew install --cask liliu-z/stashbase/stashbase
Updated
2w ago
1d ago
Open Source
Yes
Yes
Tags
Repo Intelligence, Code Graph, RAG
Local Files, RAG, AI Agents
03
Features
rag-rat01Provenance-backed Answers: Every result carries confidence labels, coverage warnings, and raw evidence from the code graph, Git history, and repo memories.
02Durable Repo Memories: Source-anchored notes (Invariant, Decision, Risk) persist across refactors and sessions, surfacing automatically during queries to provide context that traditional grep cannot.
03Comprehensive Code Graph: Builds a real code graph across multiple languages (Rust, TypeScript, Python, C/C++, Swift) with optional compiler-grade resolution for enhanced accuracy.
04Git/GitHub History as Evidence: Integrates queryable Git history, lazy blame, and cached GitHub issue/PR rationale for historical context.
05Code Duplication Detection: Warns agents about exact or near-duplicate code during writing, encouraging reuse over re-implementation.
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.
04
Use Cases
rag-rat↳Code Impact Analysis: Understand the blast radius of a code change by querying callers, callees, tests, recent commits, and associated repo memories before editing.
↳Semantic Code Search: Find specific code functionalities or concepts across source files and documentation using hybrid BM25 and vector recall.
↳Onboarding & Codebase Understanding: Identify important symbols, code clusters, and architectural decisions to quickly grasp a new repository.
↳Preventing Technical Debt: Detect and prevent code duplication during development and record durable invariants or decisions for future agents.
↳Maintaining Codebase Quality: Use `dream` to find coverage gaps in repo memories, stale references, and verify memory verdicts against current code reality.
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.
05
Best For
rag-rat—
stashbaseTrending
FAQ
FAQ
What is the difference between rag-rat and stashbase?
Both rag-rat and stashbase are in the RAG / Knowledge Base category. rag-rat has 24 stars, while stashbase has 1.1k stars.
Which is better, rag-rat or stashbase?
The best choice depends on your use case. Choose rag-rat if Code Impact Analysis: Understand the blast radius of a code change by querying callers, callees, tests, recent commits, and associated repo memories before editing., and stashbase if Providing AI agents with searchable access to research papers and contracts stored locally..
Is rag-rat free or open source?
Yes, rag-rat is open source on GitHub (MIT).
Is stashbase free or open source?
Yes, stashbase is open source on GitHub (Apache-2.0).
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