MCP server

inktomd MCP Server

io.github.hadirizvi093/inktomd-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Convert files, URLs, and documents to clean, AI-ready Markdown via MCP.

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

9

Token cost

About 1,569 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http inktomd-mcp https://mcp.inktomd.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.inktomd-mcp]
url = "https://mcp.inktomd.com/mcp"

Gemini CLI

{"mcpServers":{"inktomd-mcp":{"httpUrl":"https://mcp.inktomd.com/mcp"}}}

Cursor

{"mcpServers":{"inktomd-mcp":{"url":"https://mcp.inktomd.com/mcp"}}}

VS Code

{"servers":{"inktomd-mcp":{"type":"http","url":"https://mcp.inktomd.com/mcp"}}}

Antigravity

agy mcp add inktomd-mcp https://mcp.inktomd.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"inktomd-mcp","server_url":"https://mcp.inktomd.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"inktomd-mcp","server_url":"https://mcp.inktomd.com/mcp"}

Tools

• convert_arxiv ~142 tokens
  Convert any ArXiv research paper to clean structured Markdown. Accepts both abstract page URLs (arxiv.org/abs/PAPER_ID) and direct PDF links (arxiv.org/pdf/PAPER_ID). Returns the full paper content with headings, sections, and content preserved — uses significantly fewer tokens than the PDF format f
• convert_batch ~158 tokens
  Convert multiple URLs to Markdown in a single call. Maximum 10 URLs per batch. Each URL is converted independently. Args: urls: List of URLs to convert. Maximum 10. Each must start with http:// or https:// Returns: All converted Markdown documents combined
• convert_file ~145 tokens
  Convert a local file to clean AI-ready Markdown. Supports PDF, Word (.doc/.docx), Excel (.xls/.xlsx), PowerPoint (.ppt/.pptx), EPUB, HTML, CSV, JSON, XML, Jupyter notebooks (.ipynb), Email files (.eml/.msg), ZIP archives (.zip), and 7-Zip archives (.7z). Provide the absolute file path. Maximum file
• convert_url ~123 tokens
  Convert any URL to clean AI-ready Markdown. Supports webpages, YouTube videos, ArXiv papers, Wikipedia articles, Substack newsletters, RSS feeds, Google Docs, GitHub pages, and more. Returns Markdown with up to 63% fewer tokens than the raw source HTML.
• convert_with_metadata ~216 tokens
  Convert a file or URL to Markdown and return both content and structured metadata. Metadata includes title, estimated token counts for all major models, word count, character count, and reading time. Args: source: Either a URL (starting with http/https) or absolute file
• convert_youtube ~143 tokens
  Extract the full transcript from any public YouTube video as clean Markdown. Works with standard watch links (youtube.com/watch?v=) and short links (youtu.be/). The video must have captions enabled — including auto-generated captions. Returns the transcript as flowing Markdown paragraphs, not raw ca
• count_tokens ~224 tokens
  Count the exact number of tokens in a text string for a specific AI model. Uses tiktoken for OpenAI models and estimates for others. Args: text: The text to count tokens for model: The AI model to count tokens for. Options: gpt-4o, gpt-4o-mini, gpt-4
• list_supported_formats ~95 tokens
  List all file formats and URL types that inktomd supports for conversion to Markdown. Use this to check whether a specific file type or URL source is supported before attempting conversion.
• prepare_for_rag ~323 tokens
  Convert a file or URL to Markdown, then split it into optimally-sized chunks ready for insertion into a vector database or RAG pipeline. Returns a JSON array of chunks with token counts, making this the single tool needed to go from raw document to RAG-ready data. Args:

Browse

• Claude tools
• GitHub tools
• PDF tools
• Spreadsheets
• Word documents
• Converting to Markdown

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