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Darwin RAG MCP server

by Brightdotdev·io.github.Brightdotdev/darwin-rag·v0.2.18·3 stars
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Local-first RAG engine with MCP server for AI agent integration.

B83/100grade B
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Safety scan
B83/100

full report

Adoption
Growing

3 stars37 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Darwin RAG tools (11, 3 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • create_storewrite action

    Create a new DarwinStore at the given path for isolating data.

  • file_status

    Get detailed status for a single file across all pipeline stages.

  • get_logs

    Query Darwin session logs (oldest first for LLM readability).

  • get_schema

    Get schema information for structured files (JSON arrays, CSVs).

  • get_search_result_by_id

    Load a saved search result by its filename.

  • get_search_results

    List all saved search results.

  • list_files

    List all files tracked by a store with their pipeline status.

  • purge_artifactswrite action

    Delete pipeline artifacts for specific files.

  • run_pipelinewrite action

    Run ingestion/indexing pipeline stages.

  • search_darwin

    Search the DARWIN knowledge base for relevant passages.

  • search_lists

    Search structured data (JSON arrays, CSVs) by field values with hybrid text fallback.

Public scan report

scanner v0.1.10 · 2026-10-31 · same rubric, same numbers if you re-run it

no findings
  • Code scan176 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 17 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Darwin RAG compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
83/100
higher than 68% of 4,460 AI and agents servers
Tools
11
the typical AI and agents server has 6
Tools that change things
27%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
3
more than 75% of 2,711 AI and agents servers
Downloads a week
37
more than 28% of 1,538 AI and agents servers with a package

What its tools let an agent do: 8 read · 1 create · 1 delete · 1 run or deploy

Install Darwin RAG in Claude Code, Cursor or VS Code

claude mcp add darwin-rag -- uvx darwin-rag
Add to Cursor

What the publisher says

From the Darwin RAG repository's README, as published. We do not edit it. Read it on GitHub

<!-- 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.

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

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

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Darwin RAG: common questions

Is Darwin RAG MCP server safe?
Mostly: it is graded B (83/100). Read the Darwin RAG safety report
How do I install Darwin RAG?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Darwin RAG need an API key?
Yes. The registry entry asks for OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY.
Is Darwin RAG maintained?
The last commit was 21 days ago (2026-10-14). The latest release is v0.2.18.
What can I use instead of Darwin RAG?
Servers from other publishers that do the same job: Basic Memory MCP server, HOL Guard MCP server and Agent-Native Chat MCP server.
How does Darwin RAG compare with other AI and agents MCP servers?
safety score 83/100 (higher than 68% of 4,460 AI and agents servers); tools 11 (the typical AI and agents server has 6); tools that change things 27% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Darwin RAG

Same job from other publishers: the closest match first, then the best rated.

  • Basic Memory
    Local-first knowledge management with bi-directional LLM sync via Markdown files.
    B
  • HOL Guard
    Local-first AI agent security evidence and approval workflows through HOL Guard's stdio MCP server.
    A
  • Agent-Native Chat
    Minimal chat-first app with durable threads, actions, and the app-agent loop
    A
  • Summer Engine
    The game engine built for AI. Any agent makes a multiplayer game and publishes it.
    B
  • Local Rag
    Easy-to-setup local RAG server with minimal configuration
    A