websearch-mcp

webfetch

Fetch webpage content from any URL and process it with AI to extract summaries or answer specific questions about the page.

Instructions

Fetch a single URL, extract content, and process with LLM.

Args:
    url: The URL to fetch.
    prompt: Optional instruction for LLM processing. If omitted, provides a general summary.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "webfetch"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`prompt`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 25, 2026

TDQS

B3.3/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It discloses LLM processing and default summarization behavior when prompt is omitted. However, it lacks critical behavioral details: timeout policies, redirect handling, content size limits, or error responses.

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

Conciseness4/5

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

Front-loaded with clear action sentence followed by structured Args section. No redundant text, though the Args format is slightly technical/docstring-like rather than conversational.

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

Completeness3/5

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

Given the output schema exists, the description appropriately omits return value details. Parameter documentation is complete, but for a web-fetching tool, the absence of error handling, retry logic, or content type constraints leaves gaps.

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 has 0% description coverage (only titles). The Args section compensates by documenting both 'url' and 'prompt', including the optional status and default summary behavior of the prompt parameter. Provides sufficient semantic meaning absent from schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States specific actions (fetch, extract, process) and resource (URL). Implicitly distinguishes from sibling 'web_search' (which queries multiple sources) by emphasizing 'single URL' and LLM processing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no guidance on when to use this tool versus 'web_search' or 'image_description'. No mention of prerequisites like valid URL formats or rate limit considerations.

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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