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Octen-Team

octen-mcp

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by Octen-Team

extract

Fetch URLs and get clean, LLM-ready markdown with topic and structure classification. Optionally return relevance-ranked excerpts instead of full page body.

Instructions

Fetch one or more URLs and return LLM-ready content from Octen. By default (no query) it returns each page's full content — this is what you want in almost all cases. Only pass query when the user explicitly asks to fetch relevance-ranked snippets for a specific topic; doing so returns highlights INSTEAD of the full body, so the content will be partial. Every result also includes a category (topical) and page_structure (typology) classification, unique to Octen. Bare hosts like 'octen.ai' are auto-normalized to https. Cached when fresh.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesURLs to extract. 1-20 per call. Bare hosts ok.
queryNoOptional — leave UNSET in the normal case. When unset, each result returns the page's `full_content` (the complete text). Only set this when the user explicitly wants relevance-ranked snippets for a specific query/topic: setting it makes each result return `highlights` (ranked excerpts) and OMIT `full_content`, so the page body will be incomplete. Do not pass it just to focus a normal fetch.
formatNoOutput format. Default markdown.markdown
timeoutNoPer-URL timeout in seconds (1-60).
include_audioNoReturn audio URLs found on each page.
include_imagesNoReturn image URLs found on each page.
include_videosNoReturn video URLs found on each page.
include_faviconNoReturn each page's favicon URL.
max_age_secondsNoMaximum age of cached content in seconds. Default 24h. Lower this for time-sensitive pages (news / prices).
Behavior4/5

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

Given no annotations, the description covers key behaviors: auto-normalization of bare hosts, caching behavior, and the difference in output between default and query modes. It could be improved by mentioning error handling or rate limits, but it is sufficiently transparent.

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

Conciseness5/5

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

The description is concise and front-loaded with the main purpose. Each sentence adds value, and the paragraph is well-structured without redundancy.

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?

Despite having no output schema, the description fully explains the return structure: LLM-ready content, full_content vs highlights, and classification fields like category and page_structure. It covers all 9 parameters adequately.

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?

The description adds significant meaning beyond the input schema, such as auto-normalization of bare hosts, caching freshness behavior, and the implications of using the query parameter. This provides context that helps the agent make informed decisions.

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?

The description clearly states the verb 'Fetch' and resource 'URLs from Octen', distinguishing it from sibling search tools. It explains the default behavior (full content) and the query mode, making the tool's purpose unambiguous.

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?

The description explicitly advises against using the 'query' parameter by default and provides clear conditions for its use: only when the user explicitly asks for relevance-ranked snippets. It also warns about the trade-off (highlights instead of full content) and offers best practices.

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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