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Glama

Paypal

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. Added

TDQS

A4.9/5.0
Behavior5/5

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

Discloses data sources (SEC EDGAR, GDELT, GNews fallback, USPTO), fallback behavior (soft-fail for PatentsView sunset), and return structure (changes grouped by source, total_changes count, citation URIs). Annotations readOnlyHint, idempotentHint, etc. are consistent; no contradictions.

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 thorough but could be slightly more concise. However, it uses front-loaded examples, then sources, then parameter specifics, making it easy to scan. Every sentence adds value.

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?

Despite no output schema, the description clearly states what is returned (changes grouped by source, total_changes count, pipeworx:// citation URIs). For a read-only tool with three well-documented parameters, this is fully complete.

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 coverage is 100%, and the description adds meaningful context: explains `since` accepts ISO date or relative shorthand, `value` is ticker or CIK, `type` is only 'company'. Provides relative shorthand examples and the implication for data windowing.

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?

The description starts with concrete use-case examples ("What's new with X", "latest on Y") and explicitly distinguishes itself from the sibling tool entity_profile. It clearly states it is a change feed for a company, covering SEC filings, news, and patents.

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?

Provides explicit guidance on when to use (when asked about recent changes) and when not (for static profile, use entity_profile). Includes example query patterns and parameter suggestions like '30d' for typical monitoring.

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

All Paypal toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route broad factual questions; ai_visibility_check and scan_competitor_ai_presence overlap heavily; and the Polymarket tools blur into each other. The five PayPal tools are distinct, but the rest of the set has real boundary ambiguity.

Naming Consistency4/5

Names are almost entirely snake_case and mostly follow a verb_noun or domain_prefix pattern (paypal_*, pipeworx_*, polymarket_*). Minor deviations like entity_profile, recent_alerts, and pipeworx_feedback are noun-phrase style, but the overall convention is predictable and readable.

Tool Count1/5

A server named 'Paypal' exposes 36 tools, only five of which relate to PayPal. The remaining 31 are a grab bag of Pipeworx data lookups, Polymarket betting tools, memory helpers, and subscription utilities. This is an extreme scope mismatch for the apparent domain.

Completeness2/5

The PayPal surface is read-only: it can list/get invoices, list transactions, list disputes, and get an order, but has no create, update, send, capture, refund, or dispute-response operations. Even if the unrelated tools are ignored, a meaningful PayPal workflow is left incomplete.

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