liteparse-mcp
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": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| parse_pdfA | Parse a PDF and return structured text plus bounding boxes for every text item on every page. Bounding-box coordinates are in PDF points (1 pt = 1/72 inch), with the origin at the top-left corner of each page. Returns JSON: { "pages": [ { "page_num", "width_pts", "height_pts", "text", "text_items": [ { "text", "x", "y", "width", "height", "font_name", "font_size", "confidence" } ] } ] } |
| batch_parse_pdfsA | Parse all PDFs in a folder. For each PDF, writes to //: pages.json – text + bounding boxes per page summary.txt – plain text of the whole document page_N.png – raw page screenshot page_N_cited.png – screenshot with bounding-box highlights Returns a JSON summary of successes and any errors. |
| screenshot_pdfA | Render PDF pages as PNG images (base64-encoded). Returns JSON list of: { "page_num", "width_px", "height_px", "image_base64" } |
| cited_screenshotA | Render a single PDF page as a PNG with bounding-box highlights drawn over every extracted text item (or only items matching search_phrase). Returns JSON: { "page_num", "width_px", "height_px", "items_highlighted", "image_base64" } |
| search_pdfA | Search for a phrase in a PDF and return every matching text item with its page number and bounding-box coordinates. Returns JSON: { "phrase", "match_count", "matches": [ { "page_num", "text", "x", "y", "width", "height", "font_size" } ] } |
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 5 tools
Each tool has a clearly distinct purpose: rendering pages, extracting text with coordinates, batch processing, highlighted screenshots, and text search. No two tools serve the same function, even though two produce images, the context and output differ significantly.
All tool names are in snake_case and mostly follow a verb_noun pattern (screenshot_pdf, parse_pdf, batch_parse_pdfs, search_pdf). 'cited_screenshot' is the exception as it is a descriptive noun phrase rather than a verb_noun, but it still fits the overall naming style.
Five tools cover the core PDF parsing and rendering workflow without being excessive. Each tool addresses a distinct need, from single-page screenshots to batch processing, making the tool count well-scoped for the server's purpose.
The tool set covers the primary PDF operations: text extraction (parse_pdf), visual rendering (screenshot_pdf), highlighting (cited_screenshot), searching (search_pdf), and batch processing (batch_parse_pdfs). This is a complete lifecycle for the server's stated PDF parsing and analysis purpose.