Md2pdf Mcp

Created By
chunliu8 months ago
This server provides a tool to convert Markdown text to PDF files using the convert_markdown library. It's designed to work as an MCP (Model Context Protocol) server that can be integrated with various AI assistants and applications.
Overview

what is Md2pdf Mcp?

Md2pdf Mcp is a server tool designed to convert Markdown text into well-formatted PDF files using the convert_markdown library. It operates as an MCP (Model Context Protocol) server, allowing integration with various AI assistants and applications.

how to use Md2pdf Mcp?

To use Md2pdf Mcp, install it using uvx and configure your MCP client to connect to the server. You can then call the convert_md_to_pdf tool with your Markdown content to generate a PDF.

key features of Md2pdf Mcp?

  • Converts Markdown text to PDF files
  • Generates random filenames using UUID to prevent conflicts
  • Configurable output directory via environment variables
  • Returns resource links with metadata for easy integration
  • Built on FastMCP for reliable server functionality

use cases of Md2pdf Mcp?

  1. Converting documentation written in Markdown to PDF format for distribution.
  2. Generating reports from Markdown files for presentations.
  3. Integrating with AI applications to provide PDF outputs from user-generated Markdown content.

FAQ from Md2pdf Mcp?

  • Can Md2pdf Mcp handle large Markdown files?

Yes, it is designed to efficiently process Markdown files of various sizes.

  • Is there a limit to the number of conversions?

No, you can convert as many Markdown files as needed, subject to server capacity.

  • How do I specify the output directory for the PDFs?

You can set the PDF_OUTPUT_DIR environment variable to your desired output folder.

Server Config

{
  "mcpServers": {
    "md2pdf": {
      "command": "uvx",
      "args": [
        "--from",
        "md2pdf-mcp",
        "md2pdf"
      ],
      "env": {
        "PDF_OUTPUT_DIR": "/path/to/output/folder"
      }
    }
  }
}
Project Info
Created At
8 months ago
Updated At
7 months ago
Author Name
chunliu
Star
-
Language
-
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago
Crevio

2 days ago