links_urlReturns every internal and external link with its anchor text. Costs $0.002 USDC on Solana via x402, per call — same price as GET /api/v1/links.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The public HTTP/HTTPS URL to extract links from |
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| external | Yes | ||
| internal | Yes |
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 adds valuable behavioral context: it discloses the cost per call and the exact return content (every link and anchor text). It does not cover error handling or authentication, but the core behavior is clear.
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 sentence with front-loaded action and essential information. No wasted words, and the pricing note is concise.
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 single-parameter tool with an output schema, this description is complete: it states the return value, the resource (links), and the cost. The agent has enough to select and invoke it correctly.
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?
The input schema already fully describes the 'url' parameter with 100% coverage. The description adds no additional parameter-level details, so it stays at the baseline of 3.
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 what the tool does: 'Returns every internal and external link with its anchor text.' This is a specific verb and resource, distinguishing it from sibling tools like scrape_url or metadata_url.
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?
No explicit guidance on when to use this tool versus alternatives. The mention of pricing and an API reference does not help an agent decide between this and sibling tools.
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 targets a distinct extraction goal: specific fields, links, metadata, or full-page markdown. No overlap in purpose, so an agent can confidently select the right tool.
Naming mixes verb_noun (extract_fields, scrape_url) and noun_url (links_url, metadata_url) patterns. The _url suffix on three tools gives some cohesion, but the inconsistency is noticeable.
Four tools is a compact, focused set for a scraping server. It covers the essential extraction tasks without unnecessary bloat, though a few more specialized tools could be added.
The toolkit covers the core scraping workflow: full content, metadata, links, and targeted field extraction. Missing features like raw HTML or DOM handling are minor gaps, but most typical use cases are addressed.