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meteor-mcp

meteor-mcp

by qso-graph
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Meteor Shower Info

meteor_shower_info
Read-onlyIdempotent

Returns every published radiant and speed solution for a specified meteor shower without averaging, letting you compare original study values by code, IAU number, or name.

Instructions

Every published solution for one shower, unaveraged.

The MDC carries several solutions per shower, each from a different study, with slightly different radiants and speeds. All of them are returned. None is blended, because the average of two published radiants is a third that nobody published and no paper stands behind.

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": {
      "shower": "<shower>"
    },
    "name": "meteor_shower_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
showerYesCode, IAU number or name — "PER", "7", "Perseids", "perseid".

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavioral content beyond that: several solutions per shower, one per study, all returned, deliberately never averaged — which tells the agent what the result set will contain and why. It omits edge behavior such as an unresolvable shower code or result ordering.

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 lead sentence is front-loaded and carries the key fact in six words. The following paragraph is editorial rationale rather than instruction, but it does earn its place by justifying the no-averaging behavior rather than restating the schema.

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?

For a one-parameter lookup with an output schema and full annotation coverage, the description supplies everything an agent needs: what is returned, why it looks the way it does, and that this is a safe idempotent read. Return-value structure is correctly left to the output schema.

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% and the single shower parameter already documents accepted forms (code, IAU number, name, case variation) with examples. The description contributes no additional parameter meaning, which is acceptable at full schema coverage.

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 opening line names the resource precisely — every published solution for one shower — and the adjective "unaveraged" pins down the exact data variant returned. It does not, however, differentiate itself from plausible siblings such as meteor_source_info or meteor_activity, so the agent must infer the boundary from names alone.

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?

There is no explicit when-to-use or when-not-to-use statement and no named alternative. The rationale about not blending radiants implies the selection criterion (use this when you want raw per-study values rather than a consensus figure), but the agent has to infer it.

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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