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MCP Web Fetch Server

MCP Web Fetch Server

by narimanamiri
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

summarize_url

Fetch a URL and generate a summary using the client's language model. Specify focus and maximum length to tailor the output.

Instructions

Fetch a URL and ask the connected client's LLM (via MCP sampling) to summarize it. Requires a client that supports the sampling capability; otherwise use fetch_url and summarize the content yourself.

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": "summarize_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
focusNo
max_lengthNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the dependency on MCP sampling for summarization, which is a key behavioral trait. However, it omits details about error handling, authentication, or side effects beyond fetching.

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 action and purpose. No redundant or tangential information.

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

Completeness2/5

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

Despite having an output schema, the description does not leverage it to explain return values. It also lacks details on how optional parameters affect behavior, leaving users guessing about their function.

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

Parameters1/5

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

Schema coverage is 0% with no parameter descriptions. The description only mentions 'url' implicitly but does not explain 'focus' or 'max_length'. For a tool with 3 parameters, the description should compensate but fails to do so.

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 verb 'fetch' and 'summarize' with the resource 'URL'. It distinguishes from sibling tools like fetch_url and extract_links by specifying the summarization action via client sampling.

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

Usage Guidelines5/5

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

Provides explicit directive: requires client with sampling capability, and suggests fallback using fetch_url and manual summarization. This clearly differentiates from alternatives.

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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