io.github.hadirizvi093/inktomd-mcp
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Publisher-provided title
inktomd MCP Server
Publisher-provided description
Convert files, URLs, and documents to clean, AI-ready Markdown via MCP.
Summary by lookupd
Converts files, URLs, YouTube transcripts, and arXiv papers to Markdown, counts tokens, and chunks content for RAG pipelines.
Install
Claude Code, remote (streamable-http)
claude mcp add --transport http inktomd https://mcp.inktomd.com/mcp
Codex, remote (streamable-http)
codex mcp add inktomd --url https://mcp.inktomd.com/mcp
Cursor, remote (streamable-http) → .cursor/mcp.json
{
"mcpServers": {
"inktomd": {
"url": "https://mcp.inktomd.com/mcp"
}
}
}Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.
Tools (9 tools)
Publisher-provided text
convert_urlConvert any URL to clean AI-ready Markdown. Supports webpages, YouTube videos, ArXiv papers, Wikipedia articles, Substack newsletters, RSS feeds, Google Docs, Gconvert_fileConvert a local file to clean AI-ready Markdown. Supports PDF, Word (.doc/.docx), Excel (.xls/.xlsx), PowerPoint (.ppt/.pptx), EPUB, HTML, CSV, JSON, XML, Jupytconvert_youtubeExtract 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/).convert_arxivConvert 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/PAPElist_supported_formatsList 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 supportedcount_tokensCount the exact number of tokens in a text string for a specific AI model. Uses tiktoken for OpenAI models and estimates for others. Args:convert_batchConvert multiple URLs to Markdown in a single call. Maximum 10 URLs per batch. Each URL is converted independently. Args: urls: Listconvert_with_metadataConvert a file or URL to Markdown and return both content and structured metadata. Metadata includes title, estimated token counts for all major modelsprepare_for_ragConvert 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
Details
- Version: 1.0.0
- Transports: streamable-http
- Uptime (7 days): 100%
- Median latency: 1625 ms
- First indexed:
- Last seen in registry:
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