rag
14 MCP servers and Agent skills related to rag, each with install commands, source and popularity data, ready to paste into Cursor, Claude Code and other clients.
Local Rag Search
v0.1.0
io.clawhub.nkapila6/local-rag-search
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.
GNO
v1.2.8
io.clawhub.gmickel/gno
Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, wants to start a local web UI for their docs, or asks what was said in past coding-agent sessions.
Deep Research (Gemini)
v2.1.3
io.clawhub.24601/agent-deep-research
Async deep research via Gemini Interactions API (no Gemini CLI dependency).
Telnyx Toolkit
v1.5.0
io.clawhub.teamtelnyx/telnyx-toolkit
Complete Telnyx toolkit — ready-to-use tools (STT, TTS, RAG, Networking, 10DLC) plus SDK documentation for JavaScript, Python, Go, Java, and Ruby.
RAG Search
v0.1.1
io.clawhub.loda666/rag-search
Backend retrieval skill for structured search of occupational health standards and documents, returning relevant text with source and clause details.
Agent Docs
v1.0.0
io.clawhub.tylervovan/agent-docs
Create documentation optimized for AI agent consumption. Use when writing SKILL.md files, README files, API docs, or any documentation that will be read by LLMs in context windows. Helps structure content for RAG retrieval, token efficiency, and the Hybrid Context Hierarchy.
RAGLite
v1.0.8
io.clawhub.virajsanghvi1/raglite
Local-first RAG cache: distill docs into structured Markdown, then index/query with Chroma (vector) + ripgrep (keyword).
RAG
v1.0.2
io.clawhub.ivangdavila/rag
Designs, tunes, and debugs retrieval-augmented generation (RAG) pipelines: chunking, embeddings, hybrid retrieval, reranking, and grounded answers. Use when a system returns the wrong passages, misses a document that is indexed, cites nothing, or hallucinates over good context; when choosing a vector store, an embedding model, a chunk size, or a reranker; when similarity scores collapse after a model swap; when a metadata filter empties the result set; when answers ignore mid-context facts; when follow-up questions retrieve the wrong thing; when indexing PDFs, scanned pages, tables, code, or transcripts; when GDPR erasure, tenant isolation, or prompt injection from indexed documents is the problem; or when per-query cost or p95 latency has to come down. Covers reindex migrations, corpus freshness, evaluation sets, and agentic and graph retrieval. Not for splitter internals (`rag-chunking`), scoring rubrics (`rag-evaluation`), or LangChain APIs (`langchain`).
local-file-rag-basic
v1.0.0
io.clawhub.wjreliable/local-file-rag-basic
High-performance local File RAG suite (Basic Edition).
Jasper Recall
v0.4.0
io.clawhub.emberdesire/jasper-recall
Local retrieval-augmented generation system for AI agents using ChromaDB and sentence-transformers, supporting multi-agent shared memory and privacy controls.
Nodetool
v0.6.3
io.clawhub.georgi/nodetool
Visual AI workflow builder - ComfyUI meets n8n for LLM agents, RAG pipelines, and multimodal data flows. Local-first, open source (AGPL-3.0).
Siluzan TSO
v1.1.53
io.clawhub.sigedev01-bit/siluzan-tso
丝路赞 TSO 广告平台(Google/Bing/Yandex/TikTok/MetaAd),凡涉及丝路赞/TSO、投广告、出价预算、广告账户管理,或需要做行业分析/市场分析/行业分析报告(含「写一份 XX 行业报告」「电商/制造/医疗等行业报告」「市场调查/战略市场/KA 市场报告」「竞品/GTM/市场格局/行业趋势」等,无论是否提及丝路赞/广告/客户)须加载本 skill。【§零·最高优先】网址/域名/官网+诊断/检测/监测/评估/体检/报告/符合投放要求/能不能投(含「网络诊断」混说)→P8 website-diagnosis collect(禁纯WebFetch/肉眼看页),禁止P9/P1/W3、禁止A/B/C/D追问;细则见 intent-routing.md §零。【§零·B·次高优先】未命中§零时,行业/市场分析报告类话术→必走P9 market-analysis collect+render出HTML,禁止纯WebSearch/WebFetch在对话里写Markdown/HTML当终稿、禁止改走P8/P1/P4/W5/google-analysis;细则见 references/core/intent-routing.md §零·B。【§零·C·关键词规划】Google Ads/谷歌广告拓词、关键词规划/推荐、Keyword Planner、长尾关键词、月搜索量/搜索量、竞争度、核心词/种子词扩词(含「阅读网址/文章/页面后针对核心词出带搜索量词表」,无论是否提及丝路赞/TSO/账户)→必走W5 keyword -k … --google-only --json-out,禁止WebSearch/WebFetch编造搜索量当终稿;细则见 references/core/intent-routing.md §零·C。【报告/诊断消歧】其余报告类话术禁止默认某一CLI——行业/市场/战略/行业分析报告→P9 market-analysis(必走collect+render,禁止纯WebSearch代替);Google账户ID+健康诊断→P1 google-ads-diagnosis;只要周期数据/8维/花费转化汇总/Excel→P4;Google/谷歌广告月度报告、月总结与规划、季度报告、Q3汇总、Q4规划、季度汇报、投放季报、客户版、大族模板、下月规划→P10 google-quarterly;Met
Backboard.io
v1.0.2
io.clawhub.chrisk60331/backboard
Integrate Backboard.io for assistants, threads, memories, and document RAG via a local backend on http://localhost:5100.
volcengine-tos-vectors-skills
v1.0.2
io.clawhub.jneless/volcengine-tos-vectors-skills
Manage vector storage and similarity search using TOS Vectors service. Use when working with embeddings, semantic search, RAG systems, recommendation engines, or when the user mentions vector databases, similarity search, or TOS Vectors operations.