io.github.tidybytetools/pdf-table-pull-lite
OfficialServer 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 |
|---|---|
| extract_pdf_tablesA | Pull the tables out of a local text PDF. path: full path to a PDF on this computer. pages: optional, like "1,3-5". Empty means all pages. strategy: "auto" (default), "lines" (ruled borders) or "text" (lined up by spacing). output_dir: optional. If set, each table is saved there as a CSV and the file paths are returned. If empty, the CSV text of each table is returned. Scanned (image-only) pages have no text and are skipped. Returns [] if no tables. |
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 1 tool
There is only a single tool, so there is no possibility of selecting the wrong one. Its purpose—extracting tables from a local text PDF—is stated clearly and unambiguously.
The lone tool follows a clear snake_case verb_noun pattern (extract_pdf_tables). With one tool there is no convention mixing, and the name is self-describing.
A single tool is defensible for a deliberately 'lite', single-purpose extractor, but the surface is thin: there is no companion operation to inspect a PDF before extracting. It sits at the borderline of minimal rather than well-scoped.
The core extraction workflow is covered, including page ranges, strategy choice, and CSV output, but there are notable gaps: no way to discover page count or check whether a PDF is text-based, and scanned/image pages are simply skipped with no fallback. Agents working with real-world PDFs will hit these dead ends.