# inktomd MCP Server

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

- name: io.github.hadirizvi093/inktomd-mcp
- version: 1.0.0
- connection class: R0 (autonomous)
- trust: 73/100 flags: no-repository
- quality: 79/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.hadirizvi093%2Finktomd-mcp
- tools: https://api.protogrid.dev/v1/servers/io.github.hadirizvi093%2Finktomd-mcp/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "inktomd-mcp": {
      "type": "http",
      "url": "https://mcp.inktomd.com/mcp"
    }
  }
}
```


## Trust

- hygiene: 80
- liveness: 99
- freshness: 85
- provenance: 35
- drivers: +reachable +uptime-98% ~updated-71d-ago -no-repository
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 79/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 71 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- fail `tools.annotations`: no tool declares readOnlyHint or destructiveHint, so clients cannot tell safe calls from risky ones
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: prepare_for_rag (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); convert_url (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); convert_youtube (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 1,265 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: no tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 9, about 1,265 tokens to load them all
- tool set hash: 647e16eb85d4207af3e301c31905b354
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.hadirizvi093/inktomd-mcp.svg)](https://protogrid.dev/servers/io.github.hadirizvi093/inktomd-mcp)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

_No tool definition changes recorded._

## Remotes

- https://mcp.inktomd.com/mcp (streamable-http, auth none, reachable true, uptime30d 0.9830508)

## Packages

_none_

## Tools (9)

- `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 for AI analysis.
- `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
    
- `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.
- `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_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
    
- `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 caption fragments.
- `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
    
- `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.
- `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