RAG AI Agent Skills

Biel.ai MCP Server Connect your IDE to your product docs Give AI tools like Cursor, VS Code, and Claude Desktop access to your company's product knowledge through the Biel.ai platform. Biel.ai provides a hosted Retrieval-Augmented Generation (RAG) layer that makes your documentation searchable and useful to AI tools. This enables smarter completions, accurate technical answers, and context-aware s

👋 join us on Discord and WeChat If you like Dingo, please give us a ⭐ on GitHub! Dingo is A Comprehensive AI Data, Model and Application Quality Evaluation Tool, designed for ML practitioners, data engineers, and AI researchers. It helps you systematically assess and improve the quality of training data, fine-tuning datasets, and production AI systems. 🎯 Production-Grade Qua

Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.

RAGMap is a lightweight MCP Registry-compatible subregistry + MCP server focused on RAG-related MCP servers. - Ingests the official MCP Registry, enriches records for RAG use-cases, and serves a subregistry API. - Exposes an MCP server (remote Streamable HTTP + local stdio) so agents can search/filter RAG MCP servers. MapRag is a discovery + routing layer for retrieval. It helps agents and humans

The implementation of Model Context Protocol (MCP) server for VictoriaMetrics. This provides access to your VictoriaMetrics instance and seamless integration with VictoriaMetrics APIs and documentation. It can give you a comprehensive interface for monitoring, observability, and debugging tasks related to your VictoriaMetrics instances, enable advanced automation and interaction capabilities for e

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. - Vector-based documentation search and retrieval - Support for multiple documentation sources - Semantic search capabilities - Automated documentation processing - Real-time context augmentation f

1. 入门示例: tablestore-java-mcp-server 2. 基于 MCP 架构实现知识库答疑系统: tablestore-java-mcp-server-rag - 实现一个目前最常见的一类 AI 应用即答疑系统，支持基于私有知识库的问答，会对知识库构建和 RAG 做一些优化。 1. 入门示例: tablestore-python-mcp-server 1. Mem0-OpenMemory-MCP: tablestore-python-mem0-mcp-server 欢迎加入我们的钉钉公开群，与我们一起探讨 AI 技术。钉钉群号：36165029092

MCPServers.org | ModelScope | （更多MCP平台陆续上架中……） CRIC物业AI 是 克而瑞 专为物业行业打造的智能 AI 助理，于2025年4月25日 正式发布。 CRIC物业AI 通过行业知识库建设，结合多模态大模型 + RAG 技术，集成五大核心能力模块：行业研究、法律法规、社区治理、项目经营、文案写作，并在行业垂类知识基础上，拓展了 资讯舆情 和 人才培训 两大智能体。 克而瑞通过三个能力来构建其自身在物业AI合作领域优势： - 数据资产转化能力： 将10亿字行业语料、TB级多模态数据转化为物业行业的高质量数据集，并构建了一套行业数据质量评估体系，保障准确率和可信度； - 场景穿透能力： 聚焦20+物业行业垂直业务场景，定向选用对应领域知识库，精准匹配； - 生态进化能力： 通过每日实时监测超过500+可信资讯和数据来源，处理10万+实时数据的自更新系

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

Official OpenAI plugin with OpenAPI schema for semantic search and retrieval-augmented generation (RAG) over personal or organizational documents.

A vibe-coded memory management system with RAG capabilities for Claude via the Model Context Protocol (MCP). SimpleMem is an MCP server that provides persistent memory storage and retrieval for Claude and other MCP clients. It combines traditional file-based storage with modern RAG (Retrieval-Augmented Generation) capabilities, including semantic search and automatic relationship discovery. Think

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

Efficiently perform web searches using the mcp-local-rag server with semantic similarity ranking. Use this skill when you need to search the web for current information, research topics across multiple sources, or gather context from the internet without using external APIs. This skill teaches effective use of RAG-based web search with DuckDuckGo, Google, and multi-engine deep research capabilities.

mcp-ragchat An MCP server that adds RAG-powered AI chat to any website. One command from Claude Code. Tell Claude Code "add AI chat to mysite.com" and it will crawl your content, build a local vector store, spin up a chat server, and hand you an embed snippet. No cloud infra. No database. Just one API key. 1. Clone and build 2. Configure Claude Code (~/.claude/mcp.json) Open Claude Code and say: C

MCP Server for Driflyte. The Driflyte MCP Server exposes tools that allow AI assistants to query and retrieve topic-specific knowledge from recursively crawled and indexed web pages. With this MCP server, Driflyte acts as a bridge between diverse, topic-aware content sources (web, GitHub, and more) and AI-powered reasoning, enabling richer, more accurate answers. - Deep Web Crawling: Recursively f

Code-Graph-RAG parses a multi-language codebase with Tree-sitter, builds a knowledge graph of its structure in Memgraph, and lets you query, edit, and optimise that code in plain English. It works across a monorepo of mixed languages under one unified graph schema. - Ruby Support: Ruby joins the graph through a new pluggable ast-grep tier that adds a language from a single YAML pattern file, emitt

Comprehensive guide to implementing RAG systems including vector database selection, chunking strategies, embedding models, and retrieval optimization. Use when building RAG systems, implementing semantic search, optimizing retrieval quality, or debugging RAG performance issues.

Context compaction for AI code assistants – Give your AI structured, token-efficient access to 17+ languages including Elixir, Python, TypeScript, JavaScript, Rust, and more. Quick Install · Security · Developers · AI Assistants · Docs The core problem: AI code assistants waste context on blind searches. Grep dumps entire files when you only need a function signature, leaving less room for actual