agent-web
Server Details
URL to LLM-ready markdown - a polite, robots-respecting web reader for agents. Free.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.2/5 across 2 of 2 tools scored.
The two tools are closely related but clearly differentiated: read_url returns full markdown, while read_url_preview returns only a truncated preview. Their distinct output levels make them distinguishable, though an agent might occasionally select the wrong one if it misjudges the need for full content.
Both tool names follow a consistent 'read_url' prefix pattern with an optional 'preview' suffix. The snake_case convention is uniform and predictable, making the naming crystal clear.
With only two tools, the surface feels thin for a web-fetching server. While the tools cover basic reading (full and preview), the count is at the lower end of what is reasonable, suggesting a somewhat sparse offering.
The tool set covers the core read operation with two variations, but it explicitly lacks support for dynamic pages, PDFs, and screenshots. This creates notable gaps for agents that need those capabilities, though the server's stated purpose is focused on simple URL fetching.
Available Tools
2 toolsread_urlAInspect
Fetch one publicly reachable, server-rendered URL and return clean, LLM-ready markdown (title + word count + markdown). Polite by design: honors the origin's robots.txt for our user-agent, identifies honestly, read-only GET, never bypasses anti-bot/CAPTCHA/paywalls. Free. JavaScript-rendered pages and screenshots/PDF are not supported yet.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | absolute http(s) URL of a publicly reachable HTML page |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description thoroughly discloses behaviors: read-only GET, respects robots.txt, honest user-agent, no bypass of anti-bot/CAPTCHA/paywalls, free, and unsupported content types.
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 concise (3 sentences) and front-loaded with the core purpose. Every sentence adds essential information without 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?
For a simple tool with one parameter and no output schema, the description covers all necessary aspects: input constraints, behavior, output format, limitations, and cost.
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% with a clear parameter description. The description adds valuable context like 'server-rendered' and 'honors robots.txt', enhancing parameter understanding beyond the schema.
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 fetches a URL and returns clean markdown with title and word count. However, it does not explicitly differentiate from the sibling tool read_url_preview.
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 implies when to use (for server-rendered, public URLs) and when not (for JS-rendered pages, screenshots, PDFs), but lacks explicit guidance on when to choose this tool over read_url_preview.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_url_previewAInspect
Like read_url but returns only the first ~600 characters of the markdown (title + word count + a truncation flag) — a cheap way to check a page before pulling the full text. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | absolute http(s) URL of a publicly reachable HTML page |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses truncation behavior, return components, and cost (free). Additional details on error handling or rate limits would improve score.
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?
Single sentence plus 'Free.' is concise and front-loaded. Could be slightly more structured but efficient for the purpose.
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 simplicity (1 param, sibling tool, no output schema), the description covers key aspects: purpose, difference from sibling, and return content. Return format details are minimal but sufficient for preview.
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 covers 100% of the single parameter with adequate description. The description does not add new semantic meaning beyond what is in the schema, so baseline 3 is appropriate.
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 returns a truncated markdown preview (first ~600 chars, title, word count, truncation flag) and distinguishes it from sibling read_url by emphasizing it's a cheaper check.
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?
It indicates use for quick preview before fetching full text, implicitly contrasting with read_url. No explicit when-not-to-use, but context is clear.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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