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

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

Enables local knowledge base management with retrieval-augmented generation (RAG), providing semantic search, document reading, listing, and Q&A via MCP tools and REST endpoints, all running locally without cloud dependencies.

Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.

Bridges AI agents with watsonx.data document libraries, enabling natural language queries and intelligent retrieval from document libraries.

Enables generating images from text prompts using various AI models (FLUX, Recraft, GPT Image, etc.) and automatically delivering them through Cloudinary's platform.

Minimal local RAG stack with an MCP server that provides document search for any agent.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

A local-first RAG engine that ingests documents (PDF, Markdown, images, etc.) and provides hybrid search, reranking, and LLM answer synthesis via MCP for AI agent integration.

A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

An open-source platform for Retrieval-Augmented Generation (RAG). Upload documents and query them ⚡

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

Exposes ProsodyAI documentation, SDK references, REST API reference (OpenAPI), and curated implementation recipes to AI coding agents via MCP tools and resources.

JavaScript implementation of MiniMax MCP that enables interaction with MiniMax AI services for image generation, video generation, text-to-speech, and voice cloning through MCP-compatible clients.

Content Marketing Ideas MCP server: an editorial copilot enabling source monitoring, brief generation, voice-matched article drafting, RAG search, and WordPress publishing through natural language in Claude.

MCP server that provides tools and resources for interacting with Google Ads API, enabling search, metadata retrieval, and account management through natural language.

A Model Context Protocol server that provides Retrieval-Augmented Generation capabilities using Contextual AI, enabling AI interfaces like Cursor IDE and Claude Desktop to query domain-specific knowledge with context-aware responses and source citations.

28 tools for 3D and AR development — code generation, validation, model search (Sketchfab), and complete API reference. Android (Compose + Filament), iOS (SwiftUI + RealityKit), Web (Kotlin/JS + Filament.js). The only MCP server for 3D mobile development.

MCP server for integrating manufacturing systems (MES/ERP/quality/maintenance) with LLM agents, enabling event ingestion, incident triage, approval workflows, and RAG-based knowledge retrieval.