How do I install the Darwin RAG MCP server?

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "darwin-rag": { "command": "npx", "args": ["-y", "Darwin RAG"] } }

What does Darwin RAG do?

Local-first RAG engine with MCP server for AI agent integration.

Is the Darwin RAG MCP server free to use?

Yes. Darwin RAG is listed on AllMCPs as a free, open Model Context Protocol server you can install into Claude Desktop, Cursor, or any MCP-compatible client.

How do I install the Darwin RAG MCP server?

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "darwin-rag": { "command": "npx", "args": ["-y", "Darwin RAG"] } }

What does Darwin RAG do?

Local-first RAG engine with MCP server for AI agent integration.

Is the Darwin RAG MCP server free to use?

Yes. Darwin RAG is listed on AllMCPs as a free, open Model Context Protocol server you can install into Claude Desktop, Cursor, or any MCP-compatible client.

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.

Quick Start

1. Install

Terminal

pip install darwin-rag

2. Set up models

bash

# 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

bash

# 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:

config.json

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

Or generate config automatically:

bash

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:

bash

# 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:

config.json

{
  "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.

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.

Quick Start

1. Install

Terminal

pip install darwin-rag

2. Set up models

bash

# 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

bash

# 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:

config.json

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

Or generate config automatically:

bash

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:

bash

# 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:

config.json

{
  "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.

Darwin RAG

Quick Install

Install Config Generator

Documentation Overview

Darwin RAG

Quick Start

1. Install

2. Set up models

3. Start the MCP server & connect

MCP Tools

Remote / HTTP Mode

Environment Variables

Setup Details

CLI Reference

Documentation

Contributing

License

Related MCP Servers

Frequently Asked Questions about Darwin RAG

AllMCPs Directory Badge

Technical Specs & Signals

Feature Your MCP Server

Own this project?

Share & Embed

Explore more

Darwin RAG

Quick Install

Install Config Generator

Documentation Overview

Darwin RAG

Quick Start

1. Install

2. Set up models

3. Start the MCP server & connect

MCP Tools

Remote / HTTP Mode

Environment Variables

Setup Details

CLI Reference

Documentation

Contributing

License

Related MCP Servers

Frequently Asked Questions about Darwin RAG

AllMCPs Directory Badge

Technical Specs & Signals

Feature Your MCP Server

Own this project?

Share & Embed

Explore more