mcpcommunity/lmcc-dev-mult-fetch-mcp-server repository overview

⁠Lmcc-dev-mult-fetch-mcp-server MCP Server

A versatile MCP-compliant web content fetching tool that supports multiple modes (browser/node), formats (HTML/JSON/Markdown/Text), and intelligent proxy detection, with bilingual interface (English/Chinese).

What is an MCP Server?⁠

⁠Characteristics

Attribute	Details
Image Source	Community Image
Author	lmcc-dev⁠
Repository	https://github.com/lmcc-dev/mult-fetch-mcp-server⁠
Dockerfile	https://github.com/lmcc-dev/mult-fetch-mcp-server/blob/refs/pull/8/merge/Dockerfile⁠
Docker Image built by	Docker Inc.
Docker Scout Health Score
Licence	MIT License

⁠Available Tools

⁠Tools Details

⁠Tool: fetch_html

Fetch a website and return the content as HTML. Best practices: 1) Always set startCursor=0 for initial requests, and use the fetchedBytes value from previous response for subsequent requests to ensure content continuity. 2) Set contentSizeLimit between 20000-50000 for large pages. 3) When handling large content, use the chunking system by following the startCursor instructions in the system notes rather than increasing contentSizeLimit. 4) If content retrieval fails, you can retry using the same chunkId and startCursor, or adjust startCursor as needed but you must handle any resulting data duplication or gaps yourself. 5) Always explain to users when content is chunked and ask if they want to continue retrieving subsequent parts.

⁠Tool: fetch_json

Fetch a JSON file from a URL. Best practices: 1) Always set startCursor=0 for initial requests, and use the fetchedBytes value from previous response for subsequent requests to ensure content continuity. 2) Set contentSizeLimit between 20000-50000 for large files. 3) When handling large content, use the chunking system by following the startCursor instructions in the system notes rather than increasing contentSizeLimit. 4) If content retrieval fails, you can retry using the same chunkId and startCursor, or adjust startCursor as needed but you must handle any resulting data duplication or gaps yourself. 5) Always explain to users when content is chunked and ask if they want to continue retrieving subsequent parts.

⁠Tool: fetch_markdown

Fetch a website and return the content as Markdown. Best practices: 1) Always set startCursor=0 for initial requests, and use the fetchedBytes value from previous response for subsequent requests to ensure content continuity. 2) Set contentSizeLimit between 20000-50000 for large pages. 3) When handling large content, use the chunking system by following the startCursor instructions in the system notes rather than increasing contentSizeLimit. 4) If content retrieval fails, you can retry using the same chunkId and startCursor, or adjust startCursor as needed but you must handle any resulting data duplication or gaps yourself. 5) Always explain to users when content is chunked and ask if they want to continue retrieving subsequent parts.

⁠Tool: fetch_plaintext

Fetch a website and return the content as plain text with HTML tags removed. Best practices: 1) Always set startCursor=0 for initial requests, and use the fetchedBytes value from previous response for subsequent requests to ensure content continuity. 2) Set contentSizeLimit between 20000-50000 for large pages. 3) When handling large content, use the chunking system by following the startCursor instructions in the system notes rather than increasing contentSizeLimit. 4) If content retrieval fails, you can retry using the same chunkId and startCursor, or adjust startCursor as needed but you must handle any resulting data duplication or gaps yourself. 5) Always explain to users when content is chunked and ask if they want to continue retrieving subsequent parts.

⁠Tool: fetch_txt

Fetch a website, return the content as plain text (no HTML). Best practices: 1) Always set startCursor=0 for initial requests, and use the fetchedBytes value from previous response for subsequent requests to ensure content continuity. 2) Set contentSizeLimit between 20000-50000 for large pages. 3) When handling large content, use the chunking system by following the startCursor instructions in the system notes rather than increasing contentSizeLimit. 4) If content retrieval fails, you can retry using the same chunkId and startCursor, or adjust startCursor as needed but you must handle any resulting data duplication or gaps yourself. 5) Always explain to users when content is chunked and ask if they want to continue retrieving subsequent parts.

⁠Use this MCP Server

{
  "mcpServers": {
    "lmcc-dev-mult-fetch-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "mcpcommunity/lmcc-dev-mult-fetch-mcp-server"
      ]
    }
  }
}

Why is it safer to run MCP Servers with Docker?⁠