redd-archiver vs memory
Side-by-side comparison to help you pick between these two MCP servers.
redd-archiver by 19-84 | memory by modelcontextprotocol | |
|---|---|---|
| Stars | ★ 333 | ★ 85,748 |
| 30d uses | — | — |
| Score | 52 | 77 |
| Official | — | ✓ |
| Categories | DatabaseWeb ScrapingAI / LLM Tools | Knowledge GraphAI / 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.
memory · Summary
An MCP server implementing persistent memory using a local knowledge graph for AI models to remember user information across chats.
redd-archiver · Use cases
- Preserving internet communities before they disappear
- Creating searchable archives of historical discussions
- AI-powered analysis of archived social media content
memory · Use cases
- Personalizing AI assistant interactions by remembering user preferences, history, and relationships
- Building context-aware chat applications that maintain conversation history
- Creating knowledge bases that persist across AI model sessions
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" }
}
}
}memory · Install
Installation
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}VS Code
Use one-click installation buttons or manually configure in .vscode/mcp.json:
{
"servers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}Docker
{
"mcpServers": {
"memory": {
"command": "docker",
"args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
}
}
}