io.github.Brightdotdev/darwin-rag

io.github.Brightdotdev/darwin-rag

A local-first RAG engine that ingests documents (PDF, Markdown, images, etc.) and provides hybrid search, reranking, and LLM answer synthesis via MCP for AI agent integration.

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README

<!-- mcp-name: io.github.Brightdotdev/darwin-rag -->

Darwin RAG

A local-first RAG engine that ingests documents, indexes them with BM25 + dense embeddings, and exposes search via an MCP server for AI agent integration.

  • Ingestion — PDF, Markdown, HTML, images (OCR), CSV, Excel, ODS, URLs
  • Indexing — BM25 keyword + dense embedding hybrid index with configurable chunking strategies
  • Search — Hybrid, semantic, or keyword retrieval with reranking, diversity rerank, and structural penalties
  • Generation — LLM-backed answer synthesis via LiteLLM (OpenAI, Anthropic, Gemini, etc.)
  • Observability — Structured logging with per-session history, queryable via MCP
  • Isolation — Multiple independent stores for tenant/project separation
  • Deployment — stdio (AI agent subprocess), SSE, or Streamable HTTP; Docker-ready
  • Local-first — Everything runs locally, fully offline-capable after setup

Built by BrightDotDev.
License: MIT with Attribution


Quick Start

1. Install

pip install darwin-rag

2. Set up models

# Interactive — detects hardware, pick your models
darwin-admin setup interactive

# Or one-shot (embedding-only, no prompts)
darwin-admin setup --preset required

3. Start the MCP server & connect

# stdio mode — for AI agent subprocess (Claude Desktop, Cursor, etc.)
darwin mcp

# Or HTTP mode — for remote clients
darwin mcp --http --port 8765

Configure your MCP client:

{
  "mcpServers": {
    "darwin": {
      "command": "darwin",
      "args": ["mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-..."  // At least one LLM provider key
      }
    }
  }
}

Or generate config automatically:

darwin config claude          # Claude Desktop config
darwin config cursor          # Cursor config
darwin config all --copy      # All clients + copy to clipboard

MCP Tools

Tool Description
search_darwin Query the knowledge base with hybrid/semantic/keyword search
get_search_results List saved search results
get_search_result_by_id Load a saved search result by filename
run_pipeline Ingest + index documents from a path or URL
purge_artifacts Delete pipeline artifacts for specific files
create_store Create a new isolated data store
list_files List all tracked files with pipeline status
file_status Detailed status for a single file across all stages
get_logs Query session logs (oldest first, INFO excluded)

Full documentation: docs/mcp.md


Remote / HTTP Mode

Start the server on a network-accessible endpoint:

# SSE transport (legacy)
darwin mcp --sse --host 0.0.0.0 --port 8765

# Streamable HTTP transport (recommended for production)
darwin mcp --http --host 0.0.0.0 --port 8765

Configure your MCP client with the URL:

{
  "mcpServers": {
    "darwin": {
      "url": "http://your-host:8765/mcp"  // or /sse for SSE mode
    }
  }
}

Environment Variables

Variable Required Description
OPENAI_API_KEY No* OpenAI provider key
ANTHROPIC_API_KEY No* Anthropic provider key
GEMINI_API_KEY No* Google Gemini provider key
MISTRAL_API_KEY No* Mistral AI provider key
GROQ_API_KEY No* Groq provider key
COHERE_API_KEY No* Cohere provider key
TOGETHER_API_KEY No* Together AI provider key
OPENROUTER_API_KEY No* OpenRouter provider key
DEEPSEEK_API_KEY No* DeepSeek provider key
DARWIN_BASE_DIR No Override the base data directory
NO_COLOR No Set to any value to disable ANSI color output

* At least one LLM provider key is required for answer generation. Search/indexing works without any.


Setup Details

Command What it does
darwin-admin setup interactive Guided setup — detect hardware, choose models
darwin-admin setup --preset required Download embedding model only (fastest)
darwin-admin setup --preset recommended Embedding + reranker + OCR models
darwin-admin setup logging Reconfigure logging only
darwin-admin setup validate Validate current setup

See docs/setup.md for the full walkthrough including Docker, from-source install, and API key configuration.


CLI Reference

darwin — User CLI

Command Description
darwin mcp Start MCP server (stdio, --sse or --http for network)
darwin config [client] Generate MCP client config

darwin-admin — Power-user CLI

Command Description
darwin-admin setup Setup models, logging, and configuration
darwin-admin status System status overview
darwin-admin models Model registry: list, install, switch, keys
darwin-admin store Data store: status, files, audit, health, repair
darwin-admin pipeline Ingestion pipeline: run, ingest, index, purge
darwin-admin search Interactive search
darwin-admin logs Structured log viewer and management
darwin-admin system System information
darwin-admin uninstall Remove Darwin data and configuration

See docs/admin.md for the full command reference.


Documentation

Doc What
setup.md Full setup walkthrough
mcp.md MCP server, tools, resources, transports
admin.md Admin CLI reference
architecture.md For developers and contributors
pipeline.md Ingestion & indexing
retrieval.md Search engine
storage.md DarwinStore
models.md Model registry & inference
logger.md Structured logging
orchestrators.md High-level business logic

Contributing

Found a bug? Want to add something? You're welcome here.

  • Issues — open one at github.com/BrightDotDev/DARWIN/issues
  • Code — fork, branch, PR. Keep it minimal.
  • AI-generated code is fine — but you own what you ship. Test it before submitting.

Read CONTRIBUTING.md for the full guidelines.


License

MIT with Attribution — see LICENSE.

Core architecture and implementation by BrightDotDev.

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