Doc MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| markdown_to_pdfC | Convert markdown text into a formatted PDF. Supports: # headings, bold, - lists, 1. numbered lists,
|
| generate_pdfC | Generate a simple PDF from plain text content. |
| url_to_pdfA | Fetch a web page URL and save its content as PDF. Uses Jina AI reader to get clean markdown. |
| extract_pdf_textB | Extract text content from a PDF file. Args: source: File path, URL, or base64 PDF content |
| pdf_metadataC | Read metadata from a PDF file. |
| merge_pdfsB | Merge multiple PDF files into a single PDF. Args: sources: List of file paths, URLs, or base64 PDF contents |
| convert_textD | Text format conversion and cleanup. |
| count_wordsA | Count words, characters, lines, and paragraphs. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: text conversion, word counting, PDF extraction, PDF generation (two variants), PDF merging, metadata reading, and URL-to-PDF conversion. No two tools have overlapping functionality.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., convert_text, extract_pdf_text, merge_pdfs). The naming is predictable and easy to understand.
With 8 tools covering text conversion, word counting, and various PDF operations (extraction, generation, merging, metadata, URL conversion), the count is well-scoped for a document processing server.
Missing some common operations like converting PDFs to other formats or editing PDF content, but the set is complete for core document tasks (create, read, merge, convert, and get metadata).