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webbersites-x402-data-api

by io.github.webberdesign

post_llm

LLM INFERENCE for keyless agents — POST {prompt, system?} and get Claude Haiku's answer: summarize, classify, extract, rewrite, translate, draft. No API key, no account, no subscription — the x402 payment IS the auth. One flat price per call. Caps: 8,000-char prompt, 2,000-char system, ~1,000-token response (stop_reason tells you if you hit it). Powered by Claude Haiku 4.5. ($0.01 per call, paid via x402)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe task/question, up to 8,000 chars
systemNoOptional system prompt (persona, format rules), up to 2,000 chars

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
usageNo
responseNothe model's answer
stop_reasonNoend_turn, or max_tokens if the 1,000-token cap was hit

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

The description adds context about x402 payment, model, caps, and response indicators (stop_reason). Annotations don't contradict; readOnlyHint=false aligns with paid inference. No mention of side effects beyond charging.

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 description is a dense paragraph with each sentence adding value (purpose, payment, caps, model). Slightly long but efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description adequately covers input constraints, payment, and response size. Could mention alternatives but is sufficient for agent selection.

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%; the description repeats char limits and adds examples of use. This adds minor value beyond the schema.

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

Purpose4/5

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

The description clearly states the tool provides LLM inference using Claude Haiku, listing example use cases. However, it does not explicitly differentiate from sibling tools like post_chat or post_v1_chat_completions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for keyless agents needing quick inference without authentication, but lacks explicit when-not-to-use guidance or comparison to alternatives.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the SEO-related tools (head_check, full_audit, site_audit, etc.) overlap in scope, potentially causing confusion despite clear descriptions.

Naming Consistency5/5

Tool names consistently follow a get_/post_/delete_ verb pattern with descriptive noun phrases (e.g., get_seo_head_check, post_store_collection), with no mixing of naming conventions.

Tool Count2/5

With 46 tools covering a wide breadth of domains (SEO, accessibility, music, crypto, linting, etc.), the count is excessive for a single server, feeling unfocused and heavy.

Completeness4/5

The tool set covers most core operations for each sub-domain, but minor gaps exist (e.g., missing update for datastore, limited music operations).

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