Skip to main content
Glama

ScorpTech x402 Tools

Eol Check

eol_check
Read-onlyIdempotent

Is this software version still supported? End-of-life status from endoflife.date for 400+ products (languages, frameworks, databases, OSes, runtimes, cloud services): status (supported, security-only, eol, unmaintained), release, active-support and EOL dates, days until/since EOL, LTS flag, latest patch for the cycle and whether you are on it, the recommended upgrade cycle, and plain advice. Fuzzy product matching with suggestions; batch up to 10 product@version items. Price: $0.005 USDC per successful call (x402, Solana). Same tool over HTTPS: GET https://scorptech.it.com/api/x402/v1/eol-check

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNoBatch alternative: comma list of product@version, up to 10 (python@3.8,nodejs@18)
productNoProduct name or endoflife.date slug (python, nodejs, django, postgresql, ubuntu, ...)
versionNoVersion or release cycle (3.8, 3.8.10, 18, 22.04); omit for all current cycles

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new operational context: a $0.005 USDC x402/Solana cost per successful call and an equivalent HTTPS endpoint. Rate limits and failure/refund behavior on unsuccessful calls are not stated, keeping this short of 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?

Front-loaded with the decision-relevant question, then the return payload, then matching/batch mechanics, then pricing/endpoint. Dense but every clause carries information; the enumerated return fields make it long, though none are clearly wasteful.

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

Completeness5/5

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

With no output schema, the description must enumerate return values, and it does: status taxonomy, release, support/EOL dates, days until EOL, LTS flag, latest patch and upgrade recommendation. Combined with pricing and endpoint info, an agent has everything needed to call and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents product, version and items. The description still adds value by clarifying the batch alternative (comma list, max 10), the fuzzy-matching fallback, and that omitting version returns all current cycles.

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

Purpose5/5

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

Opens with a specific question — 'Is this software version still supported?' — and names the resource and data source (endoflife.date, 400+ products). An agent can immediately distinguish this from sibling tools like package_risk or osv_scan, which cover vulnerability risk rather than lifecycle support.

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

Usage Guidelines4/5

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

States the use case (checking support status), the batch mode limit (up to 10 product@version items), and that fuzzy matching with suggestions is available when the product name is imprecise. It does not explicitly say when to prefer this over package_risk or osv_scan, so a 4 rather than 5.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources