io.github.hadirizvi093/inktomd-mcp · v1.0.0 · productivity
inktomd MCP Server is healthy: it completed an MCP handshake in 1300 ms and exposes 9 tools.
Convert files, URLs, and documents to clean, AI-ready Markdown via MCP.
Endpoint: https://mcp.inktomd.com/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 9 |
| Latency | 1300 ms |
| Last checked (UTC) | 2026-10-16T08:10:42.485Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-16T08:10:42.485Z | Healthy | 1300 | |
| 2026-10-15T04:05:42.443Z | Healthy | 1736 |
convert_url | 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_file | 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_youtube | 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 |
convert_arxiv | 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 |
list_supported_formats | 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. |
count_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 |
convert_batch | 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_with_metadata | 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 |
prepare_for_rag | 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: |