Skip to main content
Glama
spidra-io

spidra-mcp-server

Official
by spidra-io

spidra_parse

Read-only

Convert PDF, Office, EPUB, CSV, and HTML documents into page-by-page Markdown or prompt/schema-driven JSON, with AI reading scanned pages.

Instructions

Turn documents into Markdown, page by page, and into JSON with a "prompt" or "schema". PDF, Word, Excel, PowerPoint, OpenDocument, RTF, EPUB, CSV and HTML files work, and scanned pages are read with AI.

Use it for reports, papers, invoices, contracts and spreadsheets, online or given to you as a file. Don't use it for web pages (spidra_scrape).

Send the documents one way:

  • "url": a link to one document.

  • "fileBase64" and "fileName": a file you have, base64-encoded (up to about 10 MB).

  • "fileId": a document parsed in the last 24 hours, to parse again with other options.

  • "urls" or "fileIds": several documents at once (up to 50), each parsed with the same options.

  • "pages" ("1-5, 9" or "10-") or "maxPages" parses only part of a long PDF.

  • "dryRun": true returns the page count and cost, for free, without parsing.

  • It waits up to about 50 seconds. A long document or a batch still running returns an id; check it with spidra_get_job (type "parse" or "parse_batch").

Cost: 1 credit per page parsed, plus AI credits with a prompt or schema. Formats without pages count one page per 3,000 characters. Failed pages and documents cost nothing.

Example: {"url": "https://arxiv.org/pdf/1706.03762", "pages": "1-3"}

Input Schema

NameRequiredDescriptionDefault
urlNoA link to one document
modeNo"auto" (default) uses AI only on scanned pages, "fast" never, "ocr" on every page
urlsNoLinks to several documents (a batch)
pagesNoPDF pages to parse, like "1-5, 9" or "10-"
dryRunNoReturn the pages and cost without parsing or charging
fileIdNoA fileId from a parse in the last 24 hours
promptNoFields to extract, in plain words. The result is in json.
schemaNoA JSON Schema for the answer. You get exactly these fields and types, with null for anything the page doesn't show. Define every field you want: an object with no properties comes back empty. The root must be an object.
fileIdsNoSeveral fileIds (a batch)
fileNameNoThe file's name with its extension, required with fileBase64, e.g. "report.pdf"
maxPagesNoParse at most this many pages
fileBase64NoOne file's bytes, base64-encoded (up to about 10 MB)
includePagesNoAlso return each page's Markdown on its own

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.0

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only say readOnlyHint and openWorldHint; the description adds what they cannot — the credit cost model (1 credit/page, free dryRun, failed pages free), the ~50 second wait followed by an async id checked via spidra_get_job with type 'parse'/'parse_batch', the 24-hour fileId reuse window, and the ~10 MB cap. These are exactly the operational facts an agent needs before committing to a paid, sometimes asynchronous call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the outcome, then use/don't-use, then input modes, options, cost and an example — a strong structure for a 13-parameter tool. Some sentences restate schema facts nearly verbatim (pages syntax '1-5, 9', the 10 MB base64 limit), which is mild redundancy but justified as a pre-call checklist.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex, free-form, zero-required-parameter tool with no output schema, the description covers what is missing from the structured fields: async job handoff, cost accounting, partial-document parsing, batch limits, and a concrete example call. An agent could invoke it correctly from this text alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds semantics the schema cannot express: the four input modes are mutually exclusive ('Send the documents one way'), clarifying that url/urls and fileBase64/fileIds are alternatives rather than combinable. It also explains why dryRun exists (free page count and cost preview) and that a prompt or schema switches the output shape to JSON.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Turn documents into Markdown... and into JSON') and enumerates supported formats including AI-read scanned pages. It explicitly contrasts itself with the sibling spidra_scrape, so an agent can distinguish it from every other tool in the namespace.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides an explicit 'Use it for' list (reports, papers, invoices, contracts, spreadsheets) and an explicit 'Don't use it for web pages (spidra_scrape)' exclusion with the named alternative. The input-mode section further guides selection between url/fileBase64/fileId/urls/fileIds.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.