automaton

webmd__jsonld

Convert any public web page to clean Markdown, extract HTML tables to JSON, pull JSON-LD, or crawl a whole site's sitemap and get Markdown for up to 25 pages in one call. Price: $0.01 per call in USDC on Base (eip155:8453), paid with x402 in params._meta["x402/payment"]. HTTP: GET https://api.firstmention.uk/s/webmd/jsonld

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "webmd__jsonld"
  }
}

Input Schema

Name	Required	Description
`max`	No	For /sitemap: max pages, default 10, cap 25
`url`	Yes	Public page URL
`mode`	No	Extraction mode

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedNov 6, 2026

addedInput schema / properties / max

Added value: +{
+  "description": "For /sitemap: max pages, default 10, cap 25",
+  "type": "integer"
+}

addedInput schema / properties / mode

Added value: +{
+  "description": "Extraction mode",
+  "enum": [
+    "text",
+    "article",
+    "full"
+  ],
+  "type": "string"
+}

addedInput schema / properties / url / description
```
Added value: +"Public page URL"
```
addedInput schema / properties / url / format
```
Added value: +"uri"
```
addedInput schema / required
```
Added value: +[
+  "url"
+]
```

AddedNov 2, 2026

TDQS

C2.8/5.0

Behavior3/5

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

No annotations, so the description carries the full burden. It does disclose genuinely useful non-schema behavior: a $0.01 per-call USDC charge on Base (eip155:8453) settled via x402 in params._meta, plus the exact HTTP endpoint. However it never says what a JSON-LD response looks like, what happens on pages with no JSON-LD, or whether payment failure blocks the call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single long sentence bundling four unrelated capabilities before pricing and endpoint details. It is compact and the cost/payment facts are worth including, but the lead position is spent on capabilities this specific tool does not perform, so the salient operation is buried mid-sentence.

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?

With no output schema and no annotations, the description should clarify the return shape for JSON-LD and how the 3 parameters interact with it. Instead it reuses a generic multi-mode blurb. Payment and endpoint disclosure is a real plus, but the tool-specific behavioral picture remains incomplete.

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?

Schema coverage is 100%, so the schema already documents url, mode and max (default 10, cap 25). The description's 'up to 25 pages in one call' merely restates the max cap and adds no new meaning about how mode values affect JSON-LD extraction.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names four distinct capabilities (Markdown conversion, table extraction, JSON-LD, sitemap crawl) but the tool is webmd__jsonld, and sibling tools webmd__extract, webmd__tables and webmd__sitemap exist for the other three. An agent reading this cannot tell which capability THIS endpoint performs; it appears to describe the whole family rather than the JSON-LD operation.

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?

No statement of when to use this tool versus webmd__extract, webmd__tables, webmd__sitemap, or the parallel web_extract__* and webread__* families. The only selection-adjacent text is the 25-page cap mention, which is a limit, not a routing rule.

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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