All 164 Dependencies
Every package SWIRL depends on, ranked by repo health score.
SWIRL is an open-source federated metasearch and RAG platform that distributes queries across databases, SaaS services, search engines, and enterprise apps simultaneously—without extracting, copying, or indexing any data. Instead of building a central index, SWIRL reaches out to each source at query time, collects results, and uses spaCy and NLTK to re-rank them by semantic relevance before presenting a unified view.
Designed for organizations where data sovereignty and security are non-negotiable, SWIRL supports 40+ pre-built connectors covering Microsoft 365 (SharePoint, OneDrive, Outlook, Teams), developer tools (GitHub, Jira, Confluence), databases (BigQuery, Snowflake, PostgreSQL, MongoDB), vector stores (Pinecone, Qdrant), and public sources (arXiv, Google News). Each connector is a configurable SearchProvider that maps query syntax and result fields to SWIRL's unified schema.
SWIRL adds RAG on top of federated search without requiring a separate ETL pipeline: after retrieving and re-ranking results, it passes the top documents to an OpenAI or Azure OpenAI model to generate cited, context-aware answers. This combination—real-time federation plus in-context RAG—means teams can ask questions in natural language and get answers sourced from their live internal systems.
Deployable in minutes via a single Docker Compose command, SWIRL also exposes its full capability through a REST API and a Model Context Protocol (MCP) server, making it directly accessible to AI agents like Claude Desktop, Claude Code, and Cursor—enabling them to answer questions against private enterprise sources through a standard protocol with no additional data plumbing.
