"primitive" RAG-like web search model context protocol (MCP) server that runs locally. No APIs needed.
Build and deploy pragmatic retrieval-augmented generation (RAG) agents efficiently. Integrate various data sources and APIs to enhance your AI agents' capabilities. Streamline agent development with a
An MCP server for Apify's open-source RAG Web Browser Actor to perform web searches, scrape URLs, and return content in Markdown.
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Static call graph analyzer for Go projects using SSA + VTA. Provides impact analysis, upstream/downstream queries, risk assessment, and interface tracking — so AI editors know exactly what code is aff
Find HICSS papers by topic, author, or year range. Explore sections and keywords to surface relevant research. Retrieve full document details to speed up literature reviews.
Privacy-first document search server running entirely locally. Supports semantic search over PDFs, DOCX, TXT, and Markdown files with LanceDB vector storage and local embeddings - no API keys or cloud
Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering
MCP server for Google's Gemini File Search and RAG (Retrieval-Augmented Generation). ## Features - Create and manage File Search stores - Upload documents (text, PDF, base64) with custom metada
An MCP server for accessing Vectara's trusted RAG-as-a-service platform.
A framework for creating multi-agent systems using MCP for coordinated AI collaboration, featuring task management, shared context, and RAG capabilities.
MCP server for RAGStack serverless knowledge bases. Search, chat with AI-generated answers, upload documents/media, scrape websites, and analyze metadata through an AWS-powered RAG pipeline (Lambda, B
Retrieve context from your [Ragie](https://www.ragie.ai) (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more.
Lightweight local RAG MCP server for semantic vector search over markdown documents. Reduces token consumption by 40x with sqlite-vec and multilingual-e5-small embeddings. Supports filtered search by
MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations.
Some useful tools for developer, almost everything an engineer need: confluence, Jira, Youtube, run script, knowledge base RAG, fetch URL, Manage youtube channel, emails, calendar, gitlab
LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and comp
MapRag: RAG-focused subregistry + MCP server to discover and route to retrieval-capable MCP servers using structured constraints and explainable ranking.
MCP service for Tablestore, features include adding documents, semantic search for documents based on vectors and scalars, RAG-friendly, and serverless.
Let AI tools like Cursor, VS Code, or Claude Desktop answer questions using your product docs. Biel.ai provides the RAG system and MCP server.
An MCP server for accessing all of CustomGPT.ai's anti-hallucination RAG-as-a-service API endpoints.