Convert website content to Markdown format by fetching web pages and extracting readable text, useful for content analysis, documentation, or data processing.
Fetch a website and return the content as Markdown
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the website to fetch | |
| headers | No | Optional headers to include in the request |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool fetches a website and returns Markdown, but lacks details on error handling, rate limits, authentication needs, or what happens with invalid URLs. For a tool that performs network operations with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Fetch a website and return the content as Markdown.' It is front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (network fetching with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain return values, error cases, or behavioral traits like timeouts or content conversion limitations. For a tool with no structured safety or output information, the description should provide more context to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (url and headers). The description doesn't add any meaning beyond what the schema provides, such as examples of headers or URL formats. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetch a website and return the content as Markdown.' It specifies the verb ('fetch'), resource ('website'), and output format ('Markdown'). However, it doesn't explicitly differentiate from sibling tools like fetch_html, fetch_json, and fetch_txt, which likely fetch websites but return different formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings (fetch_html, fetch_json, fetch_txt). It doesn't mention alternatives, exclusions, or specific contexts for preferring Markdown output over other formats. Usage is implied based on the need for Markdown, but no explicit guidelines are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.