automaton

webmd__tables

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/tables

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__tables"
  }
}

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

B3.1/5.0

Behavior4/5

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

With no annotations, the description carries real weight and discloses information absent from the schema: a $0.01 USDC charge on Base (eip155:8453), payment via x402 in params._meta['x402/payment'] (a field not even listed in the input schema), and the HTTP GET transport. It does not say what happens if payment is missing, whether payment is per-call or per-page, or how failures are reported, which keeps it from a 5.

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

Conciseness4/5

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

The capability list is front-loaded in the first sentence and the pricing/payment/endpoint details follow in a compact block. The HTTP endpoint string is of marginal use to an agent invoking over MCP, but on balance the text is dense and free of filler.

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?

No output schema and no annotations means the description must carry the return-value burden for a paid, multi-mode tool, yet it never says what a call returns (a Markdown string? a JSON table array? mixed per mode?) or how the four advertised capabilities are selected. The payment mechanics are covered well; the response contract is not.

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 baseline is 3. The description corroborates 'max' by stating the 25-page cap, but it adds nothing about the mode enum ('text', 'article', 'full'), which is the least self-explanatory parameter, and its mention of the table/JSON-LD functions doesn't map to any parameter.

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 concrete verbs and resources (page→Markdown, HTML tables→JSON, JSON-LD, sitemap crawl), so the general capability is clear. However, the tool is called 'tables' while the description advertises four distinct functions, and it never says which is primary or how this differs from siblings webmd__extract, webmd__jsonld and webmd__sitemap, which appear to cover exactly the same functions.

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?

There is no when-to-use, when-not-to-use, or alternative guidance at all. Given three near-identically scoped siblings in the same server family, an agent has no basis in the description for choosing this tool over webmd__extract or webmd__sitemap; the only implicit cue is 'in one call', suggesting convenience/batching.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All automaton tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?