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post_summarize_text

AI SUMMARIZATION of anything — POST {text} (16,000 chars: transcripts, threads, logs), OR {url} (web page auto-scraped, or PDF/DOCX/CSV auto-extracted), OR {file_base64} for an uploaded PDF/DOCX/CSV/TXT up to 5 MB. Keeps every load-bearing fact, number, and decision. {style}: paragraph (default), bullets, or tldr; {max_words}: 10-300 (default 120); {focus} to steer ('action items'). Want key sentences with no AI? GET /api/summarize ($0.002). ($0.01 per call, paid via x402)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoPublic http(s) URL to fetch and summarize — an article/page (main content auto-extracted) or a PDF/DOCX/CSV document
textNoRaw text to summarize, up to 16,000 characters (provide exactly one of text, url, file_base64)
typeNoOptional parser override for url/file_base64: pdf, docx, or csv
focusNoOptional steer: what the summary should emphasize
styleNoparagraph (default), bullets, or tldr
filenameNoOptional filename hint for file_base64 type detection, e.g. report.pdf
max_wordsNosummary length cap, 10-300 (default 120)
file_base64NoBase64-encoded PDF, DOCX, CSV, or plain-text file, up to 5 MB decoded (data URI prefix ok)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
styleNo
titleNo
usageNo
sourceNotext, url, or file
summaryNo
input_charsNo
source_typeNowhat was summarized: text, article, pdf, docx, or csv
input_truncatedNotrue if extracted content was cut to the summarization cap

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed10 schema fields changed
    • addedInput schema / properties / file_base64
      Added value: +{
      +  "description": "Base64-encoded PDF, DOCX, CSV, or plain-text file, up to 5 MB decoded (data URI prefix ok)",
      +  "type": "string"
      +}
    • addedInput schema / properties / filename
      Added value: +{
      +  "description": "Optional filename hint for file_base64 type detection, e.g. report.pdf",
      +  "type": "string"
      +}
    • changedInput schema / properties / text / description
      Previous value: -"The text to summarize, up to 16,000 characters"New value: +"Raw text to summarize, up to 16,000 characters (provide exactly one of text, url, file_base64)"
    • addedInput schema / properties / type
      Added value: +{
      +  "description": "Optional parser override for url/file_base64: pdf, docx, or csv",
      +  "type": "string"
      +}
    • addedInput schema / properties / url
      Added value: +{
      +  "description": "Public http(s) URL to fetch and summarize — an article/page (main content auto-extracted) or a PDF/DOCX/CSV document",
      +  "type": "string"
      +}
    • removedInput schema / required
      Removed value: -[
      -  "text"
      -]
    • addedOutput schema / properties / input_truncated
      Added value: +{
      +  "description": "true if extracted content was cut to the summarization cap",
      +  "type": "boolean"
      +}
    • addedOutput schema / properties / source
      Added value: +{
      +  "description": "text, url, or file",
      +  "type": "string"
      +}
    • addedOutput schema / properties / source_type
      Added value: +{
      +  "description": "what was summarized: text, article, pdf, docx, or csv",
      +  "type": "string"
      +}
    • addedOutput schema / properties / title
      Added value: +{
      +  "type": "string"
      +}
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Description adds cost per call ($0.01), input limits, and that it preserves load-bearing facts. Annotations indicate non-readonly and non-destructive, consistent with AI generation. No contradiction, and adds context beyond annotations.

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?

Description is dense but well-structured: starts with purpose, then inputs, style options, alternative, pricing. Every sentence adds value. Could be slightly trimmed, but overall efficient.

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?

Given 8 parameters and output schema exists, description covers core functionality, input constraints, optional parameters, and pricing. No gaps for an AI agent to select/invoke correctly.

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?

Schema covers 100% of parameters, and description enriches each: e.g., URL auto-extraction, text limit, file_base64 up to 5MB, style defaults, max_words range. Provides practical guidance beyond bare schema.

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?

Description clearly states AI summarization of text, URLs, or files. Lists specific use cases—transcripts, threads, logs, web pages, PDFs, etc.—and distinguishes from sibling GET /api/summarize. Verb 'summarize' and resource clearly identified.

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

Usage Guidelines4/5

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

Explicitly mentions when to use the GET endpoint alternative for cheaper key sentences. Provides input constraints (16k chars, 5MB). Lacks explicit when-not-to-use scenarios but the alternative covers that.

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

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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the SEO-related tools (head_check, full_audit, site_audit, etc.) overlap in scope, potentially causing confusion despite clear descriptions.

Naming Consistency5/5

Tool names consistently follow a get_/post_/delete_ verb pattern with descriptive noun phrases (e.g., get_seo_head_check, post_store_collection), with no mixing of naming conventions.

Tool Count2/5

With 46 tools covering a wide breadth of domains (SEO, accessibility, music, crypto, linting, etc.), the count is excessive for a single server, feeling unfocused and heavy.

Completeness4/5

The tool set covers most core operations for each sub-domain, but minor gaps exist (e.g., missing update for datastore, limited music operations).