Keepygaga RAG
Related Servers
Alternatives to Keepygaga RAG
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Related Servers
- FlicenseAqualityBmaintenanceEnables agents to run hybrid dense and BM25 search over a local folder of Markdown files, read and write notes, and trigger reindexing as the folder changes. It also injects the most relevant sections into each prompt automatically and runs entirely locally with a bundled embedding model.6-
- AlicenseAqualityAmaintenanceEnables coding agents to query local notes, decisions, docs, and code with hybrid retrieval (BM25 + embeddings + reranking) and get path:line citations. It provides tools like rag_query for full-corpus search and search_knowledge for project-scoped knowledge recall.21MIT
- AlicenseBqualityBmaintenanceEnables local agents to search and retrieve cited evidence from PDFs and Markdown notes, including page-specific passages and rendered page images.6GPL 3.0
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.MIT
- AlicenseAqualityAmaintenanceEnables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.101 npm1MIT
- FlicenseNot gradedqualityCmaintenanceEnables agents to search a local, fully offline personal document library (Markdown/txt/PDF/docx) via SQLite FTS5 trigram search with subject-terminology expansion, returning every hit with its domain, document title, section path, and page or offset provenance. It also exposes domain statistics, incremental ingestion, and document deprecation as tools, alongside a read-only, runtime-persona-scoped ask/coverage mode.-
TDQS
Scored across 1 tool
With only one tool exposed, there is no possible overlap or misselection between tools. The single search operation is unambiguous.
The lone tool is named with a clear, lowercase verb ('search') that accurately describes its action. There are no other names to create mixed conventions or inconsistent patterns.
A single tool is borderline: acceptable for a retrieval-only endpoint, but thin for a server branded as a RAG system, which would typically benefit from source/table discovery or management tools.
The search tool itself is feature-rich with hybrid retrieval, reranking, and filters, but the surface is incomplete for a RAG lifecycle: agents cannot ingest, update, delete, or even enumerate available sources/tables without external knowledge.