Qurio

About

Qurio is an open-source, self-hosted ingestion and retrieval engine designed to function as a local 'Shared Library' for AI agents, including tools like Cursor, Windsurf, or custom scripts. Unlike cloud-based RAG solutions, Qurio runs entirely on your machine, ingesting handpicked heterogeneous documentation such as web crawls, PDFs, and Markdown files. It serves this curated context directly to your IDE via the Model Context Protocol (MCP), enabling AI to generate more accurate code faster by relying on trusted information. Qurio emphasizes privacy by keeping your data local, enhances precision to prevent AI hallucinations, offers rapid deployment via Docker Compose, and is built on open standards like MCP, Weaviate, and PostgreSQL.

Key Features

• Universal Ingestion: Crawl documentation sites or upload files (PDF, DOCX, MD).
• Configurable Reranking: Integrate Jina AI or Cohere for precision tuning.
• Native MCP Support: Exposes a standard JSON-RPC 2.0 endpoint for seamless integration with AI coding assistants.
• OCR Pipeline: Automatically extracts text from scanned PDFs and images via Docling.
• Hybrid Search: Configurable BM25 keyword search with Vector embeddings for high-recall retrieval.
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Use Cases

• Providing grounded and private context to AI coding assistants within an IDE.
• Enhancing AI agent accuracy by ensuring responses are based on trusted, ingested content.
• Building a self-hosted knowledge base for AI agents from diverse local documentation sources.