Same as /v1/scrape/markdown plus a structured summary (≤200 words), key points and entities produced by an LLM from the page text. Price $0.04 per call, paid with USDC over x402.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | absolute https url of a public page | |
| max_chars | No |
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?
Despite having no annotations, the description discloses important behavioral details: the summary is generated by an LLM, is capped at 200 words, and the call costs $0.04 paid in USDC over x402. It does not mention failure modes, rate limits, or authentication, but the cost and processing behavior are well covered.
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?
Two sentences with no filler. It front-loads the core functional relationship, then adds the distinguishing summary output, constraints, and pricing all compactly.
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 two-parameter tool, the description plus schema is mostly sufficient. It defines the output elements, cost, and LLM behavior, though it could more explicitly describe the return structure and how max_chars influences processing. No output schema exists, so a small amount of extra output detail would make it fully complete.
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 documents url and leaves max_chars with only a range; the description adds no parameter-level meaning. 'Same as /v1/scrape/markdown' only indirectly implies shared parameters and does not explain how max_chars affects the summary or scraping. With only 50% schema description coverage, the description should compensate more but does not.
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: scrape a page like /v1/scrape/markdown and additionally produce a structured LLM-generated summary, key points, and entities. This differentiates it from sibling scrape_markdown, which presumably returns only markdown.
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 phrase 'Same as /v1/scrape/markdown plus a structured summary' implies when to choose this tool over scrape_markdown: choose this when a summary and extracted entities are needed. However, it does not explicitly state 'use this when...' or exclude cases, so it stops short of full guidance.
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.
The set splits into three clear domains, but within scraping and yields there are tiered duplicates: scrape_markdown/scrape_summary and defi_yields/yield_report overlap in output, with the latter being supersets. Descriptions clarify the differences, but an agent could still pick the wrong tier.
All tools use lowercase snake_case with descriptive, domain-prefixed names, so the convention is predictable. The only inconsistency is that scrape_* tools are verb-led while defi_* and yield_report are noun phrases, but this is a minor stylistic deviation.
Six tools is a reasonable, well-scoped set for a paid data-access server, covering fact-checking, DeFi data, and web scraping without bloat. The tiered duplicates add some redundancy but each has a distinct price/output level.
For the three apparent subdomains, the core workflows are covered: claims are checkable, DeFi protocols and yields are queryable, and pages can be scraped with or without summarization. Minor gaps exist, such as no DefiLlama protocol search by name and no batch/multi-URL operations, but agents can work around these.