Ragie

Crawl4AI RAG

Enhance your knowledge access by leveraging a cutting-edge Model Context Protocol (MCP) that combines web crawling and RAG capabilities. This innovative approach allows for seamless retrieval and storage of website content in vector databases, paving the way for advanced semantic search functionalities across crawled data.

Cloudflare AutoRAG

Elevate your AI applications with precision by implementing comprehensive RAG pipelines that are fully managed for seamless operation.

GraphRAG

Enhance your document search experience with a potent combination of Neo4j graph database and Qdrant vector database. Uncover semantic connections and expand structural context by seamlessly following relationships.

Minima (Local RAG)

Efficiently access and fetch contextual information from nearby documents for RAG applications.

Kagi Search

Enhance your workflows with cutting-edge search functions from Kagi, ensuring top-notch web data retrieval for well-informed analyses while maintaining privacy.

Apify RAG Web Browser

Utilize Apify's RAG Web Browser Actor, an open-source tool, to seamlessly conduct online searches, extract website links, and deliver information formatted in Markdown.

RAG Docs

Enhances information retrieval through semantic search functionality and a vector database (Qdrant), facilitating streamlined access to extensive document repositories.

Roam Research

Enhance your Roam Research experience with seamless integration for efficient graph content search, creation, and management. Automate note-taking and boost information retrieval with this powerful Model Context Protocol (MCP).

RAG Documentation

Experience advanced knowledge access with seamless integration of Qdrant vector search and documentation retrieval in Model Context Protocol (MCP). Unlock context-aware responses and enable semantic querying for a richer user experience.

RDF Explorer

Discover the potential of delving into RDF Knowledge Graphs with the Model Context Protocol (MCP). Unleash the power of SPARQL queries, comprehensive full-text search capabilities, and advanced visualization tools in various operational modes, including local file and endpoint settings.

Knowledge Base

Enhancing information access workflows by connecting with knowledge bases to facilitate searching, retrieving, and updating data from structured repositories.

Journal RAG

Easily search and retrieve personal notes and reflections from your markdown journal using advanced vector database technology, enhancing the way you recall past memories, ideas, and events.

Pinecone Vector DB

Utilize Pinecone's vector databases to enhance semantic search capabilities and RAG functionality.

Qdrant Knowledge Graph

Enhance your applications with seamless integration of a knowledge graph and advanced semantic search features. Streamline the storage, retrieval, and querying processes for structured data, enabling context-aware functionalities.

Qdrant Docs Rag

Efficiently capture and retrieve real-time contextual information using vector-based search with Qdrant technology.