Fetch a web page and return its main content as clean Markdown (nav, ads and boilerplate removed). Raw Markdown, plain-text and JSON endpoints are returned as-is. Use this to read an article, docs page or raw file.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The absolute http(s) URL of the page. | |
| max_chars | No | Optional. Truncate the Markdown to at most this many characters to fit a context budget. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosure and does well by stating that nav, ads, and boilerplate are removed, and that raw endpoints are returned as-is. It does not discuss error handling or rate limits, but for a read-only fetch tool the disclosed behavior is substantial.
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?
Three concise, front-loaded sentences: the main function, an important exception for raw endpoints, and a clear use case. Every sentence adds value with no redundancy.
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?
The tool is simple (2 params, no output schema) and the description explains what it returns (clean Markdown) and how raw formats are handled. It provides enough context for correct invocation and result interpretation without needing additional detail.
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 coverage is 100% and both parameters are already described in the input schema. The description adds general context but no additional syntax or meaning beyond what the schema provides, so it meets the baseline without exceeding it.
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 uses a specific verb ('Fetch a web page') and resource ('return its main content as clean Markdown'), clearly distinguishing it from sibling tools like extract_links or fetch_metadata. It also specifies the transformation (boilerplate removed) and the 'as-is' behavior for raw endpoints.
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?
Provides explicit usage guidance: 'Use this to read an article, docs page or raw file.' It does not explicitly name sibling tools as alternatives or state when not to use it, but the context is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose: extract_links returns outbound links, fetch_markdown returns content as Markdown, fetch_metadata returns page metadata, and search_page returns query-relevant passages. There is no overlap in their outputs or use cases.
All tool names follow a consistent verb_noun pattern (extract_links, fetch_markdown, fetch_metadata, search_page), making the set predictable and easy to navigate.
With 4 tools, the server is well-scoped for its purpose of web page extraction. Each tool addresses a distinct need (link crawling, content reading, metadata lookup, targeted search) without redundancy.
The tool set covers the primary ways to consume a web page—full content, links, metadata, and targeted search. A raw HTML fetch tool is missing, but fetch_markdown's handling of raw formats and JSON endpoints mitigates this gap for most use cases.