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Glama

Aviationstack

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Adds context beyond annotations: parallel fan-out to multiple sources, fallback mechanism (GDELT→GNews), soft-fail for USPTO. Describes return structure (changes[] grouped by source, total_changes, citation URIs).

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?

Single paragraph is front-loaded with query examples, but could be slightly more structured (e.g., bullet points). Still concise and efficient, no wasted words.

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?

Tool is moderately complex with multiple sources and fallback. No output schema, but description adequately explains return shape. Provides usage examples, alternative tool, and handles edge cases (USPTO soft-fail).

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

Parameters5/5

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

Schema descriptions already cover all three parameters (100% coverage). Description adds value by explaining 'since' accepts ISO or relative shorthand with examples ('7d', '30d', '3m', '1y'), and 'value' can be ticker or CIK.

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?

Description clearly states it's a change feed for a company, listing specific data sources (SEC EDGAR, GDELT→GNews, USPTO) and example queries. Distinguishes from sibling 'entity_profile' by mentioning static profile alternative.

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 explicit when-to-use examples: 'What's new with X', 'latest on Y', etc. Also provides when-not-to-use by directing to 'entity_profile' for static profiles regardless of window.

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

All Aviationstack toolsInspect
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TDQS

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and deep_research all routing queries, and the polymarket family (arbitrage, edges, edge_tracker, fill_risk) covering similar ground. While descriptions are detailed, an agent could easily select the wrong tool.

Naming Consistency2/5

Tool names mix bare nouns (airlines, airports, flights) with verb phrases (compare_entities, resolve_entity) and standalone verbs (remember, forget), with no consistent verb_noun pattern. Names like ask_pipeworx_beta and scan_competitor_ai_presence are internally inconsistent with the rest.

Tool Count2/5

37 tools is far beyond the typical scope for a single server, and many are unrelated to the aviation theme, suggesting a lack of focus. The core aviation functionality only accounts for 6 of the tools.

Completeness3/5

The aviation tools (airlines, airports, flights, routes, cities, countries) cover basic lookups, but advanced operations like delay statistics or aircraft data are absent. The unrelated tools do not fill these gaps, and the overall surface feels shallow for a server claiming to be an Aviationstack.

Resources