redd-archiver vs fetch

Side-by-side comparison to help you pick between these two MCP servers.

	redd-archiver by 19-84	fetch by modelcontextprotocol
Stars	★ 333	★ 85,748
30d uses	—	—
Score	52	76
Official	—	✓
Categories	DatabaseWeb ScrapingAI / LLM Tools	Web ScrapingAI / LLM ToolsProductivity
Language	Python	TypeScript
Last commit	1 mo ago	this month

redd-archiver · Summary

A PostgreSQL-backed archive generator that creates browsable HTML archives from link aggregator platforms with MCP server integration.

fetch · Summary

An MCP server that fetches web content and converts HTML to markdown, allowing LLMs to read web pages.

redd-archiver · Use cases

Preserving internet communities before they disappear
Creating searchable archives of historical discussions
AI-powered analysis of archived social media content

fetch · Use cases

LLMs reading news articles and blogs
Content analysis of web pages
Retrieving information from public websites
Chunked reading of large web documents

redd-archiver · Install

Installation

**Prerequisites**: Python 3.7+, PostgreSQL 12+, 4GB+ RAM

**Quick Install** (Docker):

git clone https://github.com/19-84/redd-archiver.git
cd redd-archiver

# Create required directories
mkdir -p data output/.postgres-data logs tor-public

# Configure environment (IMPORTANT: change passwords!)
cp .env.example .env
nano .env  # Edit POSTGRES_PASSWORD and DATABASE_URL

# Start services
docker compose up -d

# Generate archive (after downloading .zst files to data/)
python reddarc.py data/ \
  --subreddit privacy \
  --comments-file data/privacy_comments.zst \
  --submissions-file data/privacy_submissions.zst \
  --output output/

**MCP Server Setup for Claude Desktop**:

{
  "mcpServers": {
    "reddarchiver": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp_server", "run", "python", "server.py"],
      "env": { "REDDARCHIVER_API_URL": "http://localhost:5000" }
    }
  }
}

fetch · Install

Installation

**Using uv (recommended)** No specific installation needed. Use uvx to run the server directly:

uvx mcp-server-fetch

**Using PIP** Install via pip:

pip install mcp-server-fetch

Then run as:

python -m mcp_server_fetch

Claude Desktop Configuration

{
  "mcpServers": {
    "fetch": {
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    }
  }
}

Comparison generated from public README + GitHub signals. Last updated automatically.