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Sanoy24

safe-fetch-mcp-server

by Sanoy24

Fetch URL

fetch_url
Read-onlyIdempotent

Fetch any http(s) URL and get clean markdown output. Protects against SSRF by refusing private, loopback, and metadata addresses.

Instructions

Fetch an http(s) URL and return clean markdown. Read-only; refuses private/loopback/metadata targets by default. Args: url, format ('markdown'|'raw', default 'markdown'), max_bytes?, start_index?. Returns text content plus structuredContent {status, finalUrl, contentType, bytes, truncated}. Example: fetch_url({ url: 'https://example.com' }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute http(s) URL to fetch.
formatNoOutput format. 'markdown' (default) or 'raw' text.markdown
max_bytesNoOverride the max response size for this call.
start_indexNoByte offset for chunked reading of long pages.
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable behavioral details: it 'refuses private/loopback/metadata targets by default' and describes the structuredContent return shape (status, finalUrl, contentType, bytes, truncated). These are not present in the annotations or schema, enriching the agent's understanding of side effects and security boundaries.

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 well-structured and information-dense. It begins with purpose, then behavior/restrictions, then parameter list, then return structure, then an example. Every sentence earns its place, and the format is scannable. It is concise despite covering multiple aspects.

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

Completeness5/5

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

Given the tool's low complexity and rich schema/annotations, the description is complete: it covers the action, safety behavior, parameters, return payload, and provides an example. No output schema exists, but the description compensates by enumerating structuredContent fields. It leaves no critical gaps for an agent to invoke 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 description coverage is 100%, so the baseline is 3. The description lists args and defaults but adds no new meaning beyond the schema's per-parameter descriptions. The example call ('fetch_url({ url: 'https://example.com' })') is helpful but redundant with the schema. No extra semantics are provided for max_bytes or start_index beyond what schema already states.

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 an http(s) URL and return clean markdown.' It clearly states what the tool does and distinguishes it from any generic process by specifying the output format (markdown). It also notes the read-only nature and target restrictions, making the purpose unambiguous.

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 provides clear context on safe usage ('Read-only') and explicit restrictions ('refuses private/loopback/metadata targets by default'). While there are no sibling tools to compare against, the when-not conditions are clearly stated, offering guidance on limitations. It lacks an explicit 'use this when' statement, but the tool's niche is obvious from the purpose.

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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