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"Kotlin RAG (Retrieval-Augmented Generation) implementation resources" matching MCP servers:

  • A
    license
    Not graded
    quality
    B
    maintenance
    An evaluation harness that probes MCP-based retrieval servers for calibration, relevance, coverage, citation integrity, and more, also exposing the probes as MCP tools for assistants and CI agents.
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to search and retrieve over 89K skills on-demand at runtime, eliminating the need to manually install skills upfront.
    4
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    A minimal MCP server with a sample search_news skill that demonstrates how Claude Code can automatically call a skill over the MCP protocol.
  • F
    license
    B
    quality
    D
    maintenance
    A BM25-based MCP server that enables document search and retrieval across structured domains of knowledge content, allowing Claude to search and reference documentation when answering questions.
    4
    1
  • F
    license
    C
    quality
    D
    maintenance
    A server that implements Retrieval-Augmented Generation using GroundX and OpenAI, enabling semantic search and document retrieval with Modern Context Processing for enhanced context handling.
    3
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
    4
    Apache 2.0
  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).
    245
    36
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    A modular RAG service framework that exposes tools like query_knowledge_hub, list_collections, and get_document_summary via MCP protocol, enabling AI assistants to perform retrieval-augmented generation.
    MIT
  • A
    license
    Not graded
    quality
    F
    maintenance
    A Model Context Protocol (MCP) server with Retrieval-Augmented Generation (RAG) for answering questions about imaginary SuperNova documentation. Enables semantic search over documentation using HuggingFace embeddings.
    1
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A modular RAG (Retrieval-Augmented Generation) service framework with pluggable architecture and full observability, enabling AI assistants to perform document Q\&A, semantic search, and knowledge base construction through the Model Context Protocol.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    MCP RAG Server is a Python MCP server that indexes documents in multiple formats (Markdown, text, PowerPoint, PDF) using multilingual-e5-large embeddings and enables vector search for retrieval-augmented generation.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables Claude Desktop to search custom knowledge bases using retrieval-augmented generation via a simple MCP tool.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables retrieval-augmented generation (RAG) by indexing and searching through documents (Markdown, text, PowerPoint, PDF) using vector embeddings with multilingual-e5-large model and PostgreSQL pgvector. Supports contextual chunk retrieval and incremental indexing for efficient document management.
    71
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    An 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.
    1
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that enables RAG (Retrieval-Augmented Generation) on markdown documents by converting them to embedding vectors and performing vector search using DuckDB.
    4
    Apache 2.0