fetch-text

name	fetch-text
description	Fetch the text content of a web page or PDF from a URL. Handles HTML, PDF, Markdown, plain text — auto-detects format. Research PDFs come back as a section index you can then read section by section.
args	{"url":"required string — the URL or base64-encoded PDF to fetch","section":"optional string — for a research PDF, return just this section's text. Use a name exactly as it appeared in the section index from the first call."}

fetch-text

Retrieve and extract the text of a URL. Auto-detects the format (HTML / PDF / Markdown / plain text).

Behavior

• Research PDF (parsed into sections): the first call returns the title, the abstract, and a section index — every section name with its size — rather than the body text. Call again with the same url plus section to read one section. A long paper runs to tens of thousands of words; the index lets you read the two sections that answer the question instead of flooding the conversation with the rest.
• Other PDFs: page-by-page text extraction, truncated at 8000 chars.
• HTML: structured text with links and image references preserved.
• Markdown / plain: returned as-is.
• Page candidate images (Open Graph, Twitter cards, in-page <img> tags) are surfaced as part of the result so a downstream display can pick a primary image without re-fetching.

Reading a paper

1. {"tool": "fetch-text", "url": "<pdf url>"} → title, abstract, section index.
2. Pick the sections that bear on the question — not all of them.
3. {"tool": "fetch-text", "url": "<same url>", "section": "Results"} → that section.

Asking for a section that isn't in the index returns an error listing the names that are, so re-read the index rather than guessing. Section names match case-insensitively, and an unambiguous prefix works.

For a paper's reference list, use semantic-scholar with a paper_id — the citation graph gives resolved records, which beats parsing a bibliography out of the PDF.

When to use vs search-web

• fetch-text — you already have a specific URL and want its content.
• search-web — you're looking for information and don't yet have the URL.

Examples

{"thought": "see what's in this paper", "tool": "fetch-text", "url": "https://arxiv.org/pdf/1706.03762"}

{"thought": "the index listed a Results section — read it", "tool": "fetch-text", "url": "https://arxiv.org/pdf/1706.03762", "section": "Results"}

{"thought": "load today's weather forecast page", "tool": "fetch-text", "url": "https://forecast.weather.gov/MapClick.php?lat=37.87&lon=-122.27"}

Notes

• Section support needs a reachable GROBID server. GROBID_URL overrides the default http://localhost:8070/api/processFulltextDocument; set it to an empty string to disable. With GROBID unavailable, PDFs fall back to flat page text and the section arg has nothing to resolve against.