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smart-webfetch-mcp

smart-webfetch-mcp

by mathisto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

web_fetch_code

Extract code blocks with language annotations from documentation pages. Retrieves code examples from any URL for reuse.

Instructions

Extract only code blocks from a page. Ideal for documentation pages with code examples. Returns code blocks with language annotations.

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": "web_fetch_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesURL to extract code from
timeoutNoRequest timeout in seconds (default 30, max 120)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description must disclose behavioral traits. It mentions the output ('Returns code blocks with language annotations'), but lacks details on edge cases like pages with no code, error handling, or performance characteristics.

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 concise (two sentences) and front-loads the purpose. Every sentence adds value: the first identifies the tool, the second specifies ideal use and output. No wasted words.

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?

Given the low complexity (2 parameters, 100% schema coverage, no output schema) and clear description, the tool definition is sufficiently complete. The description explains the purpose, use case, and output format, which is enough for an agent to select and use the tool correctly.

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 coverage is 100% (both 'url' and 'timeout' are described). The description adds no additional meaning beyond the schema, as the parameter descriptions are already clear. Baseline of 3 is appropriate.

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 action ('Extract only code blocks'), the resource ('from a page'), and the context ('Ideal for documentation pages with code examples'). It also differentiates from siblings like 'web_fetch_section' and 'web_fetch_tables' by focusing specifically on code extraction.

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 explicitly states when to use this tool ('Ideal for documentation pages with code examples'), providing clear context. However, it does not mention when not to use it or explicitly compare with alternatives, which would be helpful for agent decision-making.

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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