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competlab

competlab-mcp-server

fetch_url

Read-only

Fetch any URL with automatic JavaScript rendering and bot-protection handling. Optionally strip HTML noise for efficient LLM consumption.

Instructions

Fetch any URL with automatic JS-rendering and common bot-protection handling — advanced behavioral fingerprinting may still block header retrieval (surfaced via headersAvailable: false). Returns body, headers, cleanStats. Optional cleanHtml strips HTML noise while preserving text content — token-cost win for LLM consumption.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesTarget URL. Must be http:// or https:// and resolve to a public host (IPv4/IPv6 literals and localhost are rejected).
cleanHtmlNoStrip scripts/styles/comments from text/html responses. Requires bodyNeeded. Significant token-cost reduction for LLM consumption. Default: false.
bodyNeededNoInclude body + contentType in response. Default: true.
bodyMaxBytesNoPer-request body cap in bytes. Range: 1024–104857600 (1 KiB–100 MiB).
maxTimeoutMsNoCaller timeout budget in ms. Range: 1000–120000.
headersNeededNoInclude headers + headersAvailable in response. Default: false. At least one of bodyNeeded or headersNeeded must be true.
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint), the description discloses that advanced fingerprinting may block header retrieval and flags it via headersAvailable. It also explains cleanHtml as a token-cost win for LLM. No contradictions with 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?

Two sentences, front-loaded with purpose, then critical behavioral detail. Every sentence earns its place; no fluff.

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?

No output schema, but description adequately covers return fields (body, headers, cleanStats). It mentions failure mode. Lacks explicit error handling details but sufficient for a fetch tool.

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 baseline is 3. The description adds value by explaining cleanHtml's purpose (token-cost win) and headersAvailable flag, exceeding schema info.

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 it fetches URLs with automatic JS-rendering and bot-protection handling. It distinguishes itself from siblings (e.g., check_ai_crawlers, get_tech_stack_scan) by being a generic fetcher, not domain-specific.

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 for general URL fetching with JS rendering, but does not explicitly state when not to use or compare to alternatives. However, siblings are all different domains, so context is clear.

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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