Skip to main content
Glama
mnm-matin
by mnm-matin

Fetch Webpage

fetch_webpage
Read-onlyIdempotent

Retrieve and extract clean text from web pages and PDFs, including JavaScript-rendered content, with automatic fallback to alternative extraction methods.

Instructions

Fetch and extract content from a webpage or PDF.

Uses Jina Reader to fetch and convert web pages and PDFs to clean text. Handles JavaScript-rendered pages and extracts content from PDFs. Falls back to Trafilatura extraction if Jina fails.

Args: url: The URL to fetch (web page or PDF)

Returns: Extracted content in markdown format

Examples: - Fetch a webpage: fetch_webpage("https://example.com/article") - Fetch a PDF: fetch_webpage("https://example.com/document.pdf")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch content from

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare the tool as read-only, non-destructive, and idempotent. The description adds behavioral context about Jina Reader, JavaScript handling, PDF extraction, and fallback to Trafilatura, providing useful transparency 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.

Conciseness5/5

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

The description is well-structured with clear sections (Args, Returns, Examples) and is appropriately sized for the tool's simplicity. No unnecessary words.

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 the simple single-parameter tool with an output schema, the description fully covers usage, return format, and fallback behavior. Examples further complete the picture.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaning by clarifying that the URL can be a web page or PDF and provides examples, enhancing the semantic understanding.

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 tool fetches and extracts content from web pages or PDFs, using a specific verb and resource. It distinguishes from sibling search tools by focusing on fetching a known URL rather than searching.

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?

The description implies usage when a URL is available, and examples demonstrate both web page and PDF fetches. It does not explicitly exclude alternatives, but the context of fetching a specific URL is clear relative to search tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mnm-matin/captain-search'

If you have feedback or need assistance with the MCP directory API, please join our Discord server