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maintenanceEnables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.
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Apache 2.0
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"Kotlin RAG (Retrieval-Augmented Generation) implementation resources" matching MCP servers:
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- FlicenseNot gradedqualityBmaintenanceA minimal MCP server with a sample search_news skill that demonstrates how Claude Code can automatically call a skill over the MCP protocol.
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- AlicenseNot gradedqualityCmaintenanceEnables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.MIT
- AlicenseNot gradedqualityAmaintenanceAn open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.1MIT
- FlicenseNot gradedqualityFmaintenanceEnables WordPress content management (posts, metadata, taxonomies, Gutenberg blocks) via the Model Context Protocol, demonstrating MCP Adapter integration patterns.
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- FlicenseNot gradedqualityDmaintenanceEnables semantic search and question-answering over FAQ documents using RAG (Retrieval-Augmented Generation) with OpenAI embeddings and in-memory vector similarity.
- FlicenseNot gradedqualityDmaintenanceImplements Retrieval-Augmented Generation (RAG) using GroundX and OpenAI, allowing users to ingest documents and perform semantic searches with advanced context handling through Modern Context Processing (MCP).5
- FlicenseNot gradedqualityBmaintenanceA RAG MCP server that enables retrieval-augmented question answering over PyTorch documentation, with hybrid search (FAISS+Chroma, BM25) and source-cited responses from DeepSeek.
- AlicenseAqualityCmaintenanceMCP server that integrates Apache Ranger authorization with RAG, enforcing Ranger policies to control access to knowledge bases before forwarding queries to RAG Studio.4Apache 2.0
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