Steward MCP

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steward_iss_pass

Calculate upcoming visible ISS flyover times for a given latitude and longitude from public CelesTrak orbital data for skywatching or satellite-aware scheduling.

Instructions

Upcoming visible ISS flyover times for a location, computed from public CelesTrak orbital data — skywatching or satellite-aware scheduling. Location-only sibling of steward_weather: weather for conditions, this for flyovers. Paid: $0.01 USDC on Base per call — the rail quotes each call via 402; this server verifies the quote (exact scheme, Base network, USDC, Steward payee) and settles from your wallet automatically, refusing quotes over your per-call or daily spend caps. Your payer key never leaves your machine.

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": {
      "lat": "<lat>",
      "lon": "<lon>"
    },
    "name": "steward_iss_pass"
  }
}

Input Schema

Name	Required	Description	Default
`lat`	Yes	Latitude in decimal degrees, -90 to 90 (e.g. 30.27 for Austin, TX).
`lon`	Yes	Longitude in decimal degrees, -180 to 180 (e.g. -97.74 for Austin, TX).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.1Oct 17, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does so well for the payment rail: cost ($0.01 USDC on Base), the 402 quote flow, quote verification criteria (scheme, network, token, payee), spend-cap refusal, and key custody. It omits data freshness, caching, and rate-limit behavior beyond spend caps, which keeps it 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?

Purpose is front-loaded, followed by the sibling distinction, then the payment mechanics. The final payment sentence is long and dense but every clause carries distinct information an agent needs (cost, verification, caps, custody).

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?

No output schema, but the description implies the return is flyover times, and it fully covers the payment/auth prerequisites for a paid call. For a 2-required-param read tool this is close to complete; only return-shape detail is left implicit.

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 description coverage is 100% – both lat and lon are fully documented in the schema with ranges and examples. The description adds only the word 'location', so baseline 3 is appropriate.

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?

States a specific verb and resource ('Upcoming visible ISS flyover times for a location') and names the data source (CelesTrak). It explicitly distinguishes itself from the closest sibling, steward_weather, so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

Gives concrete use cases ('skywatching or satellite-aware scheduling') and an explicit when-to-use-vs-alternative rule: 'weather for conditions, this for flyovers.' Nothing is left to inference.

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