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jcdumlao14

FastMCP Documentation & Web Scraping Server

by jcdumlao14

fetch_markdown

Extract markdown content from web pages using Jina reader API. Convert HTML to structured markdown for documentation or analysis purposes.

Instructions

Return markdown content of a web page via Jina reader.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:10-21 (handler)
    Core handler logic for the fetch_markdown tool: fetches the markdown content from a given URL using the Jina reader API, handling URL normalization.
    def fetch_markdown_impl(url: str) -> str:
        """Fetch a web page using Jina reader and return its markdown text.
    
        The Jina reader endpoint is `https://r.jina.ai/{original_url}`.
        The `url` argument may be a full URL (including scheme) or a hostname/path.
        """
        if not url.startswith("http://") and not url.startswith("https://"):
            url = "https://" + url
        target = "https://r.jina.ai/" + url
        resp = requests.get(target, timeout=15)
        resp.raise_for_status()
        return resp.text
  • main.py:25-27 (registration)
    Registration of the 'fetch_markdown' tool using the @mcp.tool decorator, including schema (url: str -> str) and docstring. Thin wrapper delegating to the impl.
    def fetch_markdown(url: str) -> str:
        """Return markdown content of a web page via Jina reader."""
        return fetch_markdown_impl(url)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'Return markdown content' and 'via Jina reader', but fails to disclose critical behavioral traits such as rate limits, authentication needs, error handling, or whether it's a read-only operation. This leaves significant gaps for a tool that interacts with external web pages.

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 a single, efficient sentence with no wasted words, clearly front-loading the purpose. Every part ('Return markdown content', 'of a web page', 'via Jina reader') adds value, making it appropriately sized and well-structured.

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 tool's complexity (fetching web content), lack of annotations, and an output schema that likely covers return values, the description is minimally complete. It states what the tool does but misses behavioral details and usage context. With an output schema, it doesn't need to explain returns, but other gaps keep it at an adequate level.

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?

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It implies the 'url' parameter is for a web page, adding some meaning beyond the bare schema. However, it doesn't specify URL format constraints, validation rules, or examples, providing only basic context. This meets the baseline for low coverage but doesn't fully address the gap.

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?

The description clearly states the action ('Return markdown content') and the resource ('of a web page'), specifying it uses 'Jina reader' as the mechanism. It distinguishes from siblings like 'add' and 'search_docs' by focusing on fetching content rather than adding or searching. However, it doesn't explicitly differentiate from potential similar tools not listed, keeping it at 4 instead of 5.

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?

The description provides no guidance on when to use this tool versus alternatives like 'search_docs' for searching documents or other web-fetching tools. It lacks context on prerequisites (e.g., URL validity), exclusions, or typical use cases, leaving the agent with minimal direction.

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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