Haiku MCP Server

Agentic Retrieval Augmented Generation (RAG) with LanceDB

What it actually does

Includes all features: document processing, all embedding providers, and rerankers.

• Hybrid search — — Vector + full-text with Reciprocal Rank Fusion
• Multimodal & cross-modal search — — Multimodal embedders (vLLM, VoyageAI, Cohere) put picture vectors in the same space as text; supports text-as-query → figure hits and image-as-query
• Question answering — — RAG capability with citations (page numbers, section headings)
• Vision QA — — Vision-capable models receive figure bytes alongside chunk text; attach your own images to questions in ask, analyze, MCP, and the chat TUI
• Reranking — — local cross-encoders, Cohere, Zero Entropy, or vLLM
• Analysis capability — — Complex analytical tasks via sandboxed Python code execution (aggregation, computation, multi-document analysis)

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Maintainer setup documentation.