Serveur MCP
inktomd MCP Server
io.github.hadirizvi093/inktomd-mcp
Ce que fait ce MCP
Converts files, webpages, videos, and research papers into structured Markdown, counts tokens, and prepares content for RAG pipelines.
Capacités
Outils
9
outils
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 â uses significantly fewer tokens than the PDF format for AI analysis.
Schéma d’entrée
{'type': 'object', 'title': 'convert_arxivArguments', 'required': ['url'], 'properties': {'url': {'type': 'string', 'title': 'Url'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_arxivOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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, clearly separated with headers
Schéma d’entrée
{'type': 'object', 'title': 'convert_batchArguments', 'required': ['urls'], 'properties': {'urls': {'type': 'array', 'items': {'type': 'string'}, 'title': 'Urls'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_batchOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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 size: 20MB.
Schéma d’entrée
{'type': 'object', 'title': 'convert_fileArguments', 'required': ['file_path'], 'properties': {'file_path': {'type': 'string', 'title': 'File Path'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_fileOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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.
Schéma d’entrée
{'type': 'object', 'title': 'convert_urlArguments', 'required': ['url'], 'properties': {'url': {'type': 'string', 'title': 'Url'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_urlOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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 path
source_type: Either "url" or "file". Default: "url"
Returns:
Markdown content with a metadata header block containing all stats
Schéma d’entrée
{'type': 'object', 'title': 'convert_with_metadataArguments', 'required': ['source'], 'properties': {'source': {'type': 'string', 'title': 'Source'}, 'source_type': {'type': 'string', 'title': 'Source Type', 'default': 'url'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_with_metadataOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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 â including auto-generated captions. Returns the transcript as flowing Markdown paragraphs, not raw caption fragments.
Schéma d’entrée
{'type': 'object', 'title': 'convert_youtubeArguments', 'required': ['url'], 'properties': {'url': {'type': 'string', 'title': 'Url'}}}
Schéma de sortie
{'type': 'object', 'title': 'convert_youtubeOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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-4.1, claude-sonnet, claude-haiku, gemini-pro, gemini-flash,
llama-4, deepseek-v3, mistral-large. Default: gpt-4o
Returns:
Token count information including count, context window, and fit status
Schéma d’entrée
{'type': 'object', 'title': 'count_tokensArguments', 'required': ['text'], 'properties': {'text': {'type': 'string', 'title': 'Text'}, 'model': {'type': 'string', 'title': 'Model', 'default': 'gpt-4o'}}}
Schéma de sortie
{'type': 'object', 'title': 'count_tokensOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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.
Schéma d’entrée
{'type': 'object', 'title': 'list_supported_formatsArguments', 'properties': {}}
Schéma de sortie
{'type': 'object', 'title': 'list_supported_formatsOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
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:
source: Either a URL (starting with http/https) or absolute file path
source_type: Either "url" or "file". Default: "url"
chunk_size: Target token count per chunk. Default: 512. Recommended range: 256-1024
overlap: Token overlap between consecutive chunks to preserve context. Default: 50
Returns:
JSON array of chunks, each with: chunk_id, text, token_count, char_count
Schéma d’entrée
{'type': 'object', 'title': 'prepare_for_ragArguments', 'required': ['source'], 'properties': {'source': {'type': 'string', 'title': 'Source'}, 'overlap': {'type': 'integer', 'title': 'Overlap', 'default': 50}, 'chunk_size': {'type': 'integer', 'title': 'Chunk Size', 'default': 512}, 'source_type': {'type': 'string', 'title': 'Source Type', 'default': 'url'}}}
Schéma de sortie
{'type': 'object', 'title': 'prepare_for_ragOutput', 'required': ['result'], 'properties': {'result': {'type': 'string', 'title': 'Result'}}}
Historique
Modifications récentes des outils
Ajouté
prepare_for_rag
17 September 2026 12:42
Ajouté
convert_with_metadata
17 September 2026 12:42
Ajouté
convert_batch
17 September 2026 12:42
Ajouté
count_tokens
17 September 2026 12:42
Ajouté
list_supported_formats
17 September 2026 12:42
Ajouté
convert_arxiv
17 September 2026 12:42
Ajouté
convert_youtube
17 September 2026 12:42
Ajouté
convert_file
17 September 2026 12:42
Ajouté
convert_url
17 September 2026 12:42
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