dompruner-mcp

Strips layout noise via DOM AST; with a query, BM25 filters to relevant sections. No model or API.

AI & MLTypeScriptv0.5.2

dompruner-mcp

한국어 | English

DOM Tree Pruning for DomPruner

DOM AST middleware for LLM web pipelines — strips layout noise (nav, scripts, sidebars) and passes original text directly. Add a query to filter to relevant sections with BM25.

When an LLM uses the built-in WebFetch, a smaller model pre-processes the HTML and hands back a summarized result — adding latency, cost, and interpretation you didn't ask for. DomPruner skips that entirely: DOM AST parsing strips noise and passes the original content directly to the model.

CallBehavior
dompruner_fetch(url)Strips layout noise → returns full extracted content
dompruner_fetch(url, query)Strips layout noise → BM25 filters to relevant sections (falls back to full content if no match)
> [DomPruner] docs.python.org
> | Raw HTML  | 44,316 tokens |
> | DomPruner |  1,328 tokens |
> | Reduction |        97.0%  |
> Fetch: 194ms · Parse: 11.2ms

93.5% fewer context tokens than WebFetch on average. 45% faster end-to-end. → Full benchmark


Quick Start

No installation, no API key:

npx -y dompruner-mcp

Claude Code

{
  "mcpServers": {
    "dompruner": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "dompruner-mcp"]
    }
  }
}

Add to .mcp.json in your project root, or ~/.claude/.mcp.json for global. Run /mcp to verify.

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "dompruner": {
      "command": "npx",
      "args": ["-y", "dompruner-mcp"]
    }
  }
}

Cursor / Windsurf / other MCP clients

{
  "mcpServers": {
    "dompruner": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "dompruner-mcp"]
    }
  }
}

Remote HTTP (no install, always up to date)

For clients that support HTTP transport — no Node.js install required, always runs the latest version:

{
  "mcpServers": {
    "dompruner": {
      "url": "https://dompruner-mcp.vercel.app/api/mcp"
    }
  }
}

LangChain / LangGraph

langchain-mcp-adapters wraps any MCP stdio server as LangChain tools automatically:

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "dompruner": {
        "command": "npx",
        "args": ["-y", "dompruner-mcp"],
        "transport": "stdio",
    }
})
tools = await client.get_tools()

Ensuring Your AI Always Uses DomPruner

DomPruner's tool description already tells clients to prefer dompruner_fetch over WebFetch. If your client still falls back, add this to its instruction file:

When retrieving a URL, always use dompruner_fetch instead of WebFetch.
- URL known → dompruner_fetch(url, query?)
- URL unknown → search for the URL first, then dompruner_fetch(url)
ClientInstruction file
Claude CodeCLAUDE.md (project) or ~/.claude/CLAUDE.md (global)
Cursor.cursorrules
Windsurf.windsurfrules
Cline.clinerules
GitHub Copilot.github/copilot-instructions.md

Tools

ToolDescription
dompruner_fetchFetch a URL → DOM-refined Markdown. Optional query enables BM25+ section filtering.
dompruner_sitemapFetch all pages in a sitemap.xml → one refined Document per page.
dompruner_analyzeToken-reduction report for a URL without full content.

→ Full tool reference


Benchmark Summary

MetricWebFetchDomPruner
Avg context tokens~15,735~1,019 (93.5% less)
Answer quality (10 queries)9 / 108 / 10
Avg response time5,811 ms3,168 ms (45% faster)
Content fidelitySummarized by small modelOriginal text preserved
Extra API key / infraNoNo

→ Full benchmark · Architecture


Related

  • dompruner-py — Python port. DomPrunerLoader, DomPrunerSitemapLoader, DomPrunerFetchTool for LangChain. pip install dompruner.
  • LangChain integrations — dompruner-py listed as a third-party web loader.

Glama Score

dompruner-mcp MCP server


License

MIT

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
npx -y dompruner-mcp

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-dong7812-dompruner-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "dompruner-mcp"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

dompruner-mcpnpm

Compatible MCP Clients

dompruner-mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More