# Run local document RAG with citations over MCP using Haiku.RAG

> Index local or self-hosted documents, search them with hybrid and multimodal retrieval, and answer agent questions through an MCP server with citations.

- Skill: `agentskillexchange/run-local-document-rag-with-citations-over-mcp-using-haiku-r` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentskillexchange/run-local-document-rag-with-citations-over-mcp-using-haiku-r`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/run-local-document-rag-with-citations-over-mcp-using-haiku-r/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: agentskillexchange (https://skillmd.com/u/agentskillexchange)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/agentskillexchange/run-local-document-rag-with-citations-over-mcp-using-haiku-r

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# Run local document RAG with citations over MCP using Haiku.RAG

Index local or self-hosted documents, search them with hybrid and multimodal retrieval, and answer agent questions through an MCP server with citations.

## Prerequisites

Python 3.12+, haiku.rag or haiku.rag-slim, an embedding provider such as Ollama/OpenAI/VoyageAI/Cohere/LM Studio/vLLM, and an MCP-compatible client

## Installation

Install or set up from the source-backed instructions:

Install with `pip install haiku.rag` or `uv pip install haiku.rag`, index documents with commands such as `haiku-rag add-src paper.pdf`, then expose the knowledge base to an MCP client with `haiku-rag mcp --stdio`. Use `haiku-rag --read-only mcp --stdio` when the agent should only search and ask questions.

- Source: https://github.com/ggozad/haiku.rag

## Documentation

- https://ggozad.github.io/haiku.rag/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/run-local-document-rag-with-citations-over-mcp-using-haiku-rag/)