A
licenseA
qualityB
maintenance"primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨
Last updated
5
126
Python
MIT
Why this server?
Though the search term 'aperag' is unclear, this server's name contains 'rag' (Retrieval-Augmented Generation), suggesting it may align with the user's intent if 'aperag' was a typo related to RAG functionality. This server focuses on local RAG-like web search.
Why this server?
This server implements Retrieval-Augmented Generation (RAG) to allow LLMs to query documents from local repositories, which might relate to the user's search if 'aperag' was a variation of RAG.
FlicenseAqualityDmaintenanceA TypeScript MCP server that allows querying documents using LLMs with context from locally stored repositories and text files through a RAG (Retrieval-Augmented Generation) system.Last updated417Why this server?
This server uses the Chroma vector database for semantic search and document management, which are core components of RAG systems, potentially matching the user's intended search domain.
-license-quality-maintenanceEnables LLMs to perform semantic search and document management using ChromaDB, supporting natural language queries with intuitive similarity metrics for retrieval augmented generation applications.Last updatedWhy this server?
This server explicitly focuses on RAG and augmenting responses with relevant documentation retrieved via vector search, fitting the theme inferred from the search query.
Alicense-qualityCmaintenanceAn MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation contextLast updated14261MITWhy this server?
This server connects a RAG application to frontends like open-webui, providing external knowledge to the model, aligning with RAG services suggested by the typo 'aperag'.
Flicense-qualityCmaintenanceConnects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).Last updated1Why this server?
Focused on RAG, this server parses documents and stores them in ChromaDB for semantic search, indicating deep capability in the Retrieval-Augmented Generation domain.
Alicense-quality-maintenanceProvides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.Last updated1116Why this server?
An alternative RAG implementation using a vector database (Qdrant) for documentation retrieval, supporting the assumption that the user was searching for a RAG tool.
Alicense-qualityDmaintenanceA Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.Last updated15135Apache 2.0Why this server?
This server integrates RAG with MCP to provide web search and document analysis capabilities for AI assistants, matching the core RAG functionality suggested by the query.
Alicense-qualityCmaintenanceA server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.Last updated4Apache 2.0Why this server?
This server focuses on document querying through a Retrieval-Augmented Generation system, offering advanced document handling via a structured architecture.
Flicense-qualityCmaintenanceAn API that enables document querying through a Retrieval-Augmented Generation system implemented with Memory-Controller-Policy architecture for improved maintainability and scalability.Last updated