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SolResearchLabs

UltraSearch MCP

by SolResearchLabs
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TypeScript
Hybrid

fetch_url

Fetch any URL and extract clean, readable markdown for research. Uses smart fallbacks for dynamic pages and GitHub, with caching and safety filters.

Instructions

Fetch and extract readable content from any URL. GitHub URLs are fetched via the GitHub API; all others go through a fetch cascade: Firecrawl → Crawl4AI → raw HTTP. Returns clean markdown where possible. Content is trimmed to a token budget (default ~2000 tokens / 8000 chars; raise with max_tokens). Results cached for 24 hours. Blocked domains and private/internal addresses are refused.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch and extract content from
max_tokensNoApproximate token budget for the returned content (chars ≈ tokens × 4). Omit for the ~2000-token / 8000-char default; max 10000 tokens.
domain_profileNoNamed domain profile to apply: 'homelab', 'dev', or omit for default filters
target_selectorNoCSS selector to scope extraction to a specific element (e.g. 'article', 'main .content'). Honored by Firecrawl/Crawl4AI and applied client-side on the raw-HTTP tier; ignored by fast paths and if it matches nothing.
wait_for_selectorNoCSS selector to wait for before extracting, for JS-rendered pages. Honored by the rendering tiers (Firecrawl/Crawl4AI); ignored on raw HTTP (no JS).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so thoroughly. It discloses the fetch mechanism (GitHub API vs. cascade), output format, token trimming with defaults, 24-hour caching, and refusal of blocked/private addresses—far beyond a minimal statement.

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?

Four dense sentences, each adding distinct value: core action, fetch pipeline, output format, and operational constraints. The most important information is front-loaded, and there is zero filler.

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

Completeness4/5

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

The description covers the essential call context: what it fetches, how it fetches, output format, size limits, caching, and restrictions. It does not describe error behavior when extraction fails, but the stated purpose and 'where possible' caveat make it adequate for a tool with no output schema.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all five parameters. The description adds marginal context (e.g., 'raise with max_tokens') but mostly restates what the schema provides, earning the baseline score for high coverage.

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 opens with a specific verb and resource: 'Fetch and extract readable content from any URL.' It clearly distinguishes itself from siblings (search, crawl_site) by focusing on single-URL retrieval and even adds method detail via the GitHub API vs. cascade distinction.

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 conveys a clear usage context: fetching a single URL and getting readable markdown. It does not explicitly name when to avoid this tool or point to alternatives like search or crawl_site, but the purpose is unambiguous enough for an agent to select it correctly.

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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